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RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Eruptive epidermoid cysts , imiquimod )",
"id": "0",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Eruptive epidermoid cysts , imiquimod )",
"output_json": "{\"relations\": [{\"head\": \"Eruptive epidermoid cysts\", \"relation\": \"adverse effect\", \"tail\": \"imiquimod\"}]}",
"sentence": "Eruptive epidermoid cysts resulting from treatment with imiquimod ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Eruptive epidermoid cysts , imiquimod )
|
Option: adverse effect
|
{"relations": [{"head": "Eruptive epidermoid cysts", "relation": "adverse effect", "tail": "imiquimod"}]}
|
( adverse effect : Eruptive epidermoid cysts , imiquimod )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nEruptive epidermoid cysts resulting from treatment with imiquimod .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Eruptive epidermoid cysts", "relation": "adverse effect", "tail": "imiquimod"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Bronchiolitis obliterans organising pneumonia , nitrofurantoin )",
"id": "1",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Bronchiolitis obliterans organising pneumonia , nitrofurantoin )",
"output_json": "{\"relations\": [{\"head\": \"Bronchiolitis obliterans organising pneumonia\", \"relation\": \"adverse effect\", \"tail\": \"nitrofurantoin\"}]}",
"sentence": "Bronchiolitis obliterans organising pneumonia associated with the use of nitrofurantoin ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Bronchiolitis obliterans organising pneumonia , nitrofurantoin )
|
Option: adverse effect
|
{"relations": [{"head": "Bronchiolitis obliterans organising pneumonia", "relation": "adverse effect", "tail": "nitrofurantoin"}]}
|
( adverse effect : Bronchiolitis obliterans organising pneumonia , nitrofurantoin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nBronchiolitis obliterans organising pneumonia associated with the use of nitrofurantoin .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Bronchiolitis obliterans organising pneumonia", "relation": "adverse effect", "tail": "nitrofurantoin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : overanticoagulation , acenocoumarol )",
"id": "2",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : overanticoagulation , acenocoumarol )",
"output_json": "{\"relations\": [{\"head\": \"overanticoagulation\", \"relation\": \"adverse effect\", \"tail\": \"acenocoumarol\"}]}",
"sentence": "We report the case of a young healthy woman who presented an early overanticoagulation when receiving acenocoumarol for a first thromboembolic episode ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : overanticoagulation , acenocoumarol )
|
Option: adverse effect
|
{"relations": [{"head": "overanticoagulation", "relation": "adverse effect", "tail": "acenocoumarol"}]}
|
( adverse effect : overanticoagulation , acenocoumarol )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nWe report the case of a young healthy woman who presented an early overanticoagulation when receiving acenocoumarol for a first thromboembolic episode .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "overanticoagulation", "relation": "adverse effect", "tail": "acenocoumarol"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : angioedema , aspirin ) ; ( adverse effect : systemic anaphylactoid reaction , aspirin ) ; ( adverse effect : urticaria , aspirin )",
"id": "3",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : angioedema , aspirin ) ; ( adverse effect : systemic anaphylactoid reaction , aspirin ) ; ( adverse effect : urticaria , aspirin )",
"output_json": "{\"relations\": [{\"head\": \"angioedema\", \"relation\": \"adverse effect\", \"tail\": \"aspirin\"}, {\"head\": \"systemic anaphylactoid reaction\", \"relation\": \"adverse effect\", \"tail\": \"aspirin\"}, {\"head\": \"urticaria\", \"relation\": \"adverse effect\", \"tail\": \"aspirin\"}]}",
"sentence": "Hypersensitivity to aspirin can be manifested as acute asthma , urticaria and/or angioedema , or a systemic anaphylactoid reaction ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : angioedema , aspirin ) ; ( adverse effect : systemic anaphylactoid reaction , aspirin ) ; ( adverse effect : urticaria , aspirin )
|
Option: adverse effect
|
{"relations": [{"head": "angioedema", "relation": "adverse effect", "tail": "aspirin"}, {"head": "systemic anaphylactoid reaction", "relation": "adverse effect", "tail": "aspirin"}, {"head": "urticaria", "relation": "adverse effect", "tail": "aspirin"}]}
|
( adverse effect : angioedema , aspirin ) ; ( adverse effect : systemic anaphylactoid reaction , aspirin ) ; ( adverse effect : urticaria , aspirin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nHypersensitivity to aspirin can be manifested as acute asthma , urticaria and/or angioedema , or a systemic anaphylactoid reaction .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "angioedema", "relation": "adverse effect", "tail": "aspirin"}, {"head": "systemic anaphylactoid reaction", "relation": "adverse effect", "tail": "aspirin"}, {"head": "urticaria", "relation": "adverse effect", "tail": "aspirin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : severe hypersensitivity , carboplatin )",
"id": "4",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : severe hypersensitivity , carboplatin )",
"output_json": "{\"relations\": [{\"head\": \"severe hypersensitivity\", \"relation\": \"adverse effect\", \"tail\": \"carboplatin\"}]}",
"sentence": "Prick tests and intradermal tests with a series of dilutions of carboplatin and cisplatin were performed on three patients who had exhibited medium and severe hypersensitivity reactions to carboplatin ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : severe hypersensitivity , carboplatin )
|
Option: adverse effect
|
{"relations": [{"head": "severe hypersensitivity", "relation": "adverse effect", "tail": "carboplatin"}]}
|
( adverse effect : severe hypersensitivity , carboplatin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nPrick tests and intradermal tests with a series of dilutions of carboplatin and cisplatin were performed on three patients who had exhibited medium and severe hypersensitivity reactions to carboplatin .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "severe hypersensitivity", "relation": "adverse effect", "tail": "carboplatin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : nephropathy , gold - salt )",
"id": "5",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : nephropathy , gold - salt )",
"output_json": "{\"relations\": [{\"head\": \"nephropathy\", \"relation\": \"adverse effect\", \"tail\": \"gold - salt\"}]}",
"sentence": "Although the data indicate an immune - complex cause for gold - salt nephropathy , the incident antigen ( or antigens ) and mechanism of action remain unidentified ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : nephropathy , gold - salt )
|
Option: adverse effect
|
{"relations": [{"head": "nephropathy", "relation": "adverse effect", "tail": "gold - salt"}]}
|
( adverse effect : nephropathy , gold - salt )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nAlthough the data indicate an immune - complex cause for gold - salt nephropathy , the incident antigen ( or antigens ) and mechanism of action remain unidentified .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "nephropathy", "relation": "adverse effect", "tail": "gold - salt"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : neurologic events , Phenylpropanolamine ) ; ( adverse effect : neurologic events , PPA ) ; ( adverse effect : stroke , Phenylpropanolamine ) ; ( adverse effect : stroke , PPA )",
"id": "6",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : neurologic events , Phenylpropanolamine ) ; ( adverse effect : neurologic events , PPA ) ; ( adverse effect : stroke , Phenylpropanolamine ) ; ( adverse effect : stroke , PPA )",
"output_json": "{\"relations\": [{\"head\": \"neurologic events\", \"relation\": \"adverse effect\", \"tail\": \"Phenylpropanolamine\"}, {\"head\": \"neurologic events\", \"relation\": \"adverse effect\", \"tail\": \"PPA\"}, {\"head\": \"stroke\", \"relation\": \"adverse effect\", \"tail\": \"Phenylpropanolamine\"}, {\"head\": \"stroke\", \"relation\": \"adverse effect\", \"tail\": \"PPA\"}]}",
"sentence": "Phenylpropanolamine ( PPA ) recently has been publicly implicated as a cause of stroke and other neurologic events ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : neurologic events , Phenylpropanolamine ) ; ( adverse effect : neurologic events , PPA ) ; ( adverse effect : stroke , Phenylpropanolamine ) ; ( adverse effect : stroke , PPA )
|
Option: adverse effect
|
{"relations": [{"head": "neurologic events", "relation": "adverse effect", "tail": "Phenylpropanolamine"}, {"head": "neurologic events", "relation": "adverse effect", "tail": "PPA"}, {"head": "stroke", "relation": "adverse effect", "tail": "Phenylpropanolamine"}, {"head": "stroke", "relation": "adverse effect", "tail": "PPA"}]}
|
( adverse effect : neurologic events , Phenylpropanolamine ) ; ( adverse effect : neurologic events , PPA ) ; ( adverse effect : stroke , Phenylpropanolamine ) ; ( adverse effect : stroke , PPA )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nPhenylpropanolamine ( PPA ) recently has been publicly implicated as a cause of stroke and other neurologic events .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "neurologic events", "relation": "adverse effect", "tail": "Phenylpropanolamine"}, {"head": "neurologic events", "relation": "adverse effect", "tail": "PPA"}, {"head": "stroke", "relation": "adverse effect", "tail": "Phenylpropanolamine"}, {"head": "stroke", "relation": "adverse effect", "tail": "PPA"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : eosinophilia , propylthiouracil ) ; ( adverse effect : granulocytopenia , propylthiouracil ) ; ( adverse effect : hepatitis , propylthiouracil ) ; ( adverse effect : lymphocyte sensitization , propylthiouracil ) ; ( adverse effect : skin reaction , propylthiouracil )",
"id": "7",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : eosinophilia , propylthiouracil ) ; ( adverse effect : granulocytopenia , propylthiouracil ) ; ( adverse effect : hepatitis , propylthiouracil ) ; ( adverse effect : lymphocyte sensitization , propylthiouracil ) ; ( adverse effect : skin reaction , propylthiouracil )",
"output_json": "{\"relations\": [{\"head\": \"eosinophilia\", \"relation\": \"adverse effect\", \"tail\": \"propylthiouracil\"}, {\"head\": \"granulocytopenia\", \"relation\": \"adverse effect\", \"tail\": \"propylthiouracil\"}, {\"head\": \"hepatitis\", \"relation\": \"adverse effect\", \"tail\": \"propylthiouracil\"}, {\"head\": \"lymphocyte sensitization\", \"relation\": \"adverse effect\", \"tail\": \"propylthiouracil\"}, {\"head\": \"skin reaction\", \"relation\": \"adverse effect\", \"tail\": \"propylthiouracil\"}]}",
"sentence": "Multiple complications of propylthiouracil treatment : granulocytopenia , eosinophilia , skin reaction and hepatitis with lymphocyte sensitization ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : eosinophilia , propylthiouracil ) ; ( adverse effect : granulocytopenia , propylthiouracil ) ; ( adverse effect : hepatitis , propylthiouracil ) ; ( adverse effect : lymphocyte sensitization , propylthiouracil ) ; ( adverse effect : skin reaction , propylthiouracil )
|
Option: adverse effect
|
{"relations": [{"head": "eosinophilia", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "granulocytopenia", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "hepatitis", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "lymphocyte sensitization", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "skin reaction", "relation": "adverse effect", "tail": "propylthiouracil"}]}
|
( adverse effect : eosinophilia , propylthiouracil ) ; ( adverse effect : granulocytopenia , propylthiouracil ) ; ( adverse effect : hepatitis , propylthiouracil ) ; ( adverse effect : lymphocyte sensitization , propylthiouracil ) ; ( adverse effect : skin reaction , propylthiouracil )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nMultiple complications of propylthiouracil treatment : granulocytopenia , eosinophilia , skin reaction and hepatitis with lymphocyte sensitization .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "eosinophilia", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "granulocytopenia", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "hepatitis", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "lymphocyte sensitization", "relation": "adverse effect", "tail": "propylthiouracil"}, {"head": "skin reaction", "relation": "adverse effect", "tail": "propylthiouracil"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : hyperthyroidism , IFN - alpha )",
"id": "8",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : hyperthyroidism , IFN - alpha )",
"output_json": "{\"relations\": [{\"head\": \"hyperthyroidism\", \"relation\": \"adverse effect\", \"tail\": \"IFN - alpha\"}]}",
"sentence": "Hence , hyperthyroidism induced by IFN - alpha could correspond to the first phase of silent thyroiditis , to Graves ' disease or to the succession of both ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : hyperthyroidism , IFN - alpha )
|
Option: adverse effect
|
{"relations": [{"head": "hyperthyroidism", "relation": "adverse effect", "tail": "IFN - alpha"}]}
|
( adverse effect : hyperthyroidism , IFN - alpha )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nHence , hyperthyroidism induced by IFN - alpha could correspond to the first phase of silent thyroiditis , to Graves ' disease or to the succession of both .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "hyperthyroidism", "relation": "adverse effect", "tail": "IFN - alpha"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : hypersensitivity , carboplatin )",
"id": "9",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : hypersensitivity , carboplatin )",
"output_json": "{\"relations\": [{\"head\": \"hypersensitivity\", \"relation\": \"adverse effect\", \"tail\": \"carboplatin\"}]}",
"sentence": "This regimen could prove useful for other patients who develop hypersensitivity reactions to carboplatin and allow therapy to continue ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : hypersensitivity , carboplatin )
|
Option: adverse effect
|
{"relations": [{"head": "hypersensitivity", "relation": "adverse effect", "tail": "carboplatin"}]}
|
( adverse effect : hypersensitivity , carboplatin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThis regimen could prove useful for other patients who develop hypersensitivity reactions to carboplatin and allow therapy to continue .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "hypersensitivity", "relation": "adverse effect", "tail": "carboplatin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : QT prolongation , pirmenol ) ; ( adverse effect : T wave inversion , pirmenol )",
"id": "10",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : QT prolongation , pirmenol ) ; ( adverse effect : T wave inversion , pirmenol )",
"output_json": "{\"relations\": [{\"head\": \"QT prolongation\", \"relation\": \"adverse effect\", \"tail\": \"pirmenol\"}, {\"head\": \"T wave inversion\", \"relation\": \"adverse effect\", \"tail\": \"pirmenol\"}]}",
"sentence": "Thus , an immunological mechanism might be involved in the mechanism of pirmenol - induced QT prolongation and T wave inversion on the electrocardiogram ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : QT prolongation , pirmenol ) ; ( adverse effect : T wave inversion , pirmenol )
|
Option: adverse effect
|
{"relations": [{"head": "QT prolongation", "relation": "adverse effect", "tail": "pirmenol"}, {"head": "T wave inversion", "relation": "adverse effect", "tail": "pirmenol"}]}
|
( adverse effect : QT prolongation , pirmenol ) ; ( adverse effect : T wave inversion , pirmenol )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThus , an immunological mechanism might be involved in the mechanism of pirmenol - induced QT prolongation and T wave inversion on the electrocardiogram .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "QT prolongation", "relation": "adverse effect", "tail": "pirmenol"}, {"head": "T wave inversion", "relation": "adverse effect", "tail": "pirmenol"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : urinary calculus , Magnesium )",
"id": "11",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : urinary calculus , Magnesium )",
"output_json": "{\"relations\": [{\"head\": \"urinary calculus\", \"relation\": \"adverse effect\", \"tail\": \"Magnesium\"}]}",
"sentence": "Magnesium tocolysis as the cause of urinary calculus during pregnancy ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : urinary calculus , Magnesium )
|
Option: adverse effect
|
{"relations": [{"head": "urinary calculus", "relation": "adverse effect", "tail": "Magnesium"}]}
|
( adverse effect : urinary calculus , Magnesium )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nMagnesium tocolysis as the cause of urinary calculus during pregnancy .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "urinary calculus", "relation": "adverse effect", "tail": "Magnesium"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : tuberculosis , Efalizumab ) ; ( adverse effect : tuberculosis , Etanercept )",
"id": "12",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : tuberculosis , Efalizumab ) ; ( adverse effect : tuberculosis , Etanercept )",
"output_json": "{\"relations\": [{\"head\": \"tuberculosis\", \"relation\": \"adverse effect\", \"tail\": \"Efalizumab\"}, {\"head\": \"tuberculosis\", \"relation\": \"adverse effect\", \"tail\": \"Etanercept\"}]}",
"sentence": "A case of tuberculosis in a patient on Efalizumab and Etanercept for treatment of refractory palmopustular psoriasis and psoriatic arthritis ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : tuberculosis , Efalizumab ) ; ( adverse effect : tuberculosis , Etanercept )
|
Option: adverse effect
|
{"relations": [{"head": "tuberculosis", "relation": "adverse effect", "tail": "Efalizumab"}, {"head": "tuberculosis", "relation": "adverse effect", "tail": "Etanercept"}]}
|
( adverse effect : tuberculosis , Efalizumab ) ; ( adverse effect : tuberculosis , Etanercept )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nA case of tuberculosis in a patient on Efalizumab and Etanercept for treatment of refractory palmopustular psoriasis and psoriatic arthritis .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "tuberculosis", "relation": "adverse effect", "tail": "Efalizumab"}, {"head": "tuberculosis", "relation": "adverse effect", "tail": "Etanercept"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Hashimoto 's disease , IFN - alpha ) ; ( adverse effect : Hashimoto 's disease , interferon - alpha )",
"id": "13",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Hashimoto 's disease , IFN - alpha ) ; ( adverse effect : Hashimoto 's disease , interferon - alpha )",
"output_json": "{\"relations\": [{\"head\": \"Hashimoto 's disease\", \"relation\": \"adverse effect\", \"tail\": \"IFN - alpha\"}, {\"head\": \"Hashimoto 's disease\", \"relation\": \"adverse effect\", \"tail\": \"interferon - alpha\"}]}",
"sentence": "OBJECTIVES : The authors described a case of Hashimoto 's disease during interferon - alpha ( IFN - alpha ) treatment for chronic viral C hepatitis in a patient with the specific genetic susceptibility associated with the thyroid disease ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Hashimoto 's disease , IFN - alpha ) ; ( adverse effect : Hashimoto 's disease , interferon - alpha )
|
Option: adverse effect
|
{"relations": [{"head": "Hashimoto 's disease", "relation": "adverse effect", "tail": "IFN - alpha"}, {"head": "Hashimoto 's disease", "relation": "adverse effect", "tail": "interferon - alpha"}]}
|
( adverse effect : Hashimoto 's disease , IFN - alpha ) ; ( adverse effect : Hashimoto 's disease , interferon - alpha )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nOBJECTIVES : The authors described a case of Hashimoto 's disease during interferon - alpha ( IFN - alpha ) treatment for chronic viral C hepatitis in a patient with the specific genetic susceptibility associated with the thyroid disease .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Hashimoto 's disease", "relation": "adverse effect", "tail": "IFN - alpha"}, {"head": "Hashimoto 's disease", "relation": "adverse effect", "tail": "interferon - alpha"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Hepatic damage , danazol )",
"id": "14",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Hepatic damage , danazol )",
"output_json": "{\"relations\": [{\"head\": \"Hepatic damage\", \"relation\": \"adverse effect\", \"tail\": \"danazol\"}]}",
"sentence": "Hepatic damage after danazol treatment ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Hepatic damage , danazol )
|
Option: adverse effect
|
{"relations": [{"head": "Hepatic damage", "relation": "adverse effect", "tail": "danazol"}]}
|
( adverse effect : Hepatic damage , danazol )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nHepatic damage after danazol treatment .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Hepatic damage", "relation": "adverse effect", "tail": "danazol"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : maculopathy , Niacin )",
"id": "15",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : maculopathy , Niacin )",
"output_json": "{\"relations\": [{\"head\": \"maculopathy\", \"relation\": \"adverse effect\", \"tail\": \"Niacin\"}]}",
"sentence": "Niacin maculopathy ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : maculopathy , Niacin )
|
Option: adverse effect
|
{"relations": [{"head": "maculopathy", "relation": "adverse effect", "tail": "Niacin"}]}
|
( adverse effect : maculopathy , Niacin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nNiacin maculopathy .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "maculopathy", "relation": "adverse effect", "tail": "Niacin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Angioedema , budesonide ) ; ( adverse effect : dysphagia , budesonide )",
"id": "16",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Angioedema , budesonide ) ; ( adverse effect : dysphagia , budesonide )",
"output_json": "{\"relations\": [{\"head\": \"Angioedema\", \"relation\": \"adverse effect\", \"tail\": \"budesonide\"}, {\"head\": \"dysphagia\", \"relation\": \"adverse effect\", \"tail\": \"budesonide\"}]}",
"sentence": "Angioedema and dysphagia caused by contact allergy to inhaled budesonide ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Angioedema , budesonide ) ; ( adverse effect : dysphagia , budesonide )
|
Option: adverse effect
|
{"relations": [{"head": "Angioedema", "relation": "adverse effect", "tail": "budesonide"}, {"head": "dysphagia", "relation": "adverse effect", "tail": "budesonide"}]}
|
( adverse effect : Angioedema , budesonide ) ; ( adverse effect : dysphagia , budesonide )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nAngioedema and dysphagia caused by contact allergy to inhaled budesonide .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Angioedema", "relation": "adverse effect", "tail": "budesonide"}, {"head": "dysphagia", "relation": "adverse effect", "tail": "budesonide"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : disfiguring facial edema , peginterferon alfa-2a ) ; ( adverse effect : disfiguring facial edema , ribavirin )",
"id": "17",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : disfiguring facial edema , peginterferon alfa-2a ) ; ( adverse effect : disfiguring facial edema , ribavirin )",
"output_json": "{\"relations\": [{\"head\": \"disfiguring facial edema\", \"relation\": \"adverse effect\", \"tail\": \"peginterferon alfa-2a\"}, {\"head\": \"disfiguring facial edema\", \"relation\": \"adverse effect\", \"tail\": \"ribavirin\"}]}",
"sentence": "OBSERVATIONS : A 48-year - old woman presented with disfiguring facial edema 10 weeks after she began antiviral therapy with peginterferon alfa-2a and ribavirin for chronic hepatitis C infection ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : disfiguring facial edema , peginterferon alfa-2a ) ; ( adverse effect : disfiguring facial edema , ribavirin )
|
Option: adverse effect
|
{"relations": [{"head": "disfiguring facial edema", "relation": "adverse effect", "tail": "peginterferon alfa-2a"}, {"head": "disfiguring facial edema", "relation": "adverse effect", "tail": "ribavirin"}]}
|
( adverse effect : disfiguring facial edema , peginterferon alfa-2a ) ; ( adverse effect : disfiguring facial edema , ribavirin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nOBSERVATIONS : A 48-year - old woman presented with disfiguring facial edema 10 weeks after she began antiviral therapy with peginterferon alfa-2a and ribavirin for chronic hepatitis C infection .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "disfiguring facial edema", "relation": "adverse effect", "tail": "peginterferon alfa-2a"}, {"head": "disfiguring facial edema", "relation": "adverse effect", "tail": "ribavirin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : pulmonary vasoconstriction , protamine ) ; ( adverse effect : right ventricular failure , protamine )",
"id": "18",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : pulmonary vasoconstriction , protamine ) ; ( adverse effect : right ventricular failure , protamine )",
"output_json": "{\"relations\": [{\"head\": \"pulmonary vasoconstriction\", \"relation\": \"adverse effect\", \"tail\": \"protamine\"}, {\"head\": \"right ventricular failure\", \"relation\": \"adverse effect\", \"tail\": \"protamine\"}]}",
"sentence": "A case report is presented concerning the administration of ketanserin in the treatment of pulmonary vasoconstriction and right ventricular failure following the infusion of protamine in a patient undergoing coronary artery bypass surgery and mitral valve replacement ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : pulmonary vasoconstriction , protamine ) ; ( adverse effect : right ventricular failure , protamine )
|
Option: adverse effect
|
{"relations": [{"head": "pulmonary vasoconstriction", "relation": "adverse effect", "tail": "protamine"}, {"head": "right ventricular failure", "relation": "adverse effect", "tail": "protamine"}]}
|
( adverse effect : pulmonary vasoconstriction , protamine ) ; ( adverse effect : right ventricular failure , protamine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nA case report is presented concerning the administration of ketanserin in the treatment of pulmonary vasoconstriction and right ventricular failure following the infusion of protamine in a patient undergoing coronary artery bypass surgery and mitral valve replacement .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "pulmonary vasoconstriction", "relation": "adverse effect", "tail": "protamine"}, {"head": "right ventricular failure", "relation": "adverse effect", "tail": "protamine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Fatal pulmonary fibrosis , BCNU )",
"id": "19",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Fatal pulmonary fibrosis , BCNU )",
"output_json": "{\"relations\": [{\"head\": \"Fatal pulmonary fibrosis\", \"relation\": \"adverse effect\", \"tail\": \"BCNU\"}]}",
"sentence": "Fatal pulmonary fibrosis associated with BCNU : the relative role of platelet - derived growth factor - B , insulin - like growth factor I , transforming growth factor - beta1 and cyclooxygenase-2 ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Fatal pulmonary fibrosis , BCNU )
|
Option: adverse effect
|
{"relations": [{"head": "Fatal pulmonary fibrosis", "relation": "adverse effect", "tail": "BCNU"}]}
|
( adverse effect : Fatal pulmonary fibrosis , BCNU )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nFatal pulmonary fibrosis associated with BCNU : the relative role of platelet - derived growth factor - B , insulin - like growth factor I , transforming growth factor - beta1 and cyclooxygenase-2 .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Fatal pulmonary fibrosis", "relation": "adverse effect", "tail": "BCNU"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Syncope , nitrate )",
"id": "20",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Syncope , nitrate )",
"output_json": "{\"relations\": [{\"head\": \"Syncope\", \"relation\": \"adverse effect\", \"tail\": \"nitrate\"}]}",
"sentence": "Syncope in a 65-year - old woman after nitrate ingestion ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Syncope , nitrate )
|
Option: adverse effect
|
{"relations": [{"head": "Syncope", "relation": "adverse effect", "tail": "nitrate"}]}
|
( adverse effect : Syncope , nitrate )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nSyncope in a 65-year - old woman after nitrate ingestion .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Syncope", "relation": "adverse effect", "tail": "nitrate"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : morphea , bromocriptine )",
"id": "21",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : morphea , bromocriptine )",
"output_json": "{\"relations\": [{\"head\": \"morphea\", \"relation\": \"adverse effect\", \"tail\": \"bromocriptine\"}]}",
"sentence": "A 57-year - old man developed morphea while taking bromocriptine ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : morphea , bromocriptine )
|
Option: adverse effect
|
{"relations": [{"head": "morphea", "relation": "adverse effect", "tail": "bromocriptine"}]}
|
( adverse effect : morphea , bromocriptine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nA 57-year - old man developed morphea while taking bromocriptine .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "morphea", "relation": "adverse effect", "tail": "bromocriptine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : cardiac arrhythmias , amphotericin B ) ; ( adverse effect : mortality , amphotericin B )",
"id": "22",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : cardiac arrhythmias , amphotericin B ) ; ( adverse effect : mortality , amphotericin B )",
"output_json": "{\"relations\": [{\"head\": \"cardiac arrhythmias\", \"relation\": \"adverse effect\", \"tail\": \"amphotericin B\"}, {\"head\": \"mortality\", \"relation\": \"adverse effect\", \"tail\": \"amphotericin B\"}]}",
"sentence": "Hydrocortisone may decrease the incidence of mortality associated with cardiac arrhythmias in children receiving amphotericin B overdoses ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : cardiac arrhythmias , amphotericin B ) ; ( adverse effect : mortality , amphotericin B )
|
Option: adverse effect
|
{"relations": [{"head": "cardiac arrhythmias", "relation": "adverse effect", "tail": "amphotericin B"}, {"head": "mortality", "relation": "adverse effect", "tail": "amphotericin B"}]}
|
( adverse effect : cardiac arrhythmias , amphotericin B ) ; ( adverse effect : mortality , amphotericin B )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nHydrocortisone may decrease the incidence of mortality associated with cardiac arrhythmias in children receiving amphotericin B overdoses .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "cardiac arrhythmias", "relation": "adverse effect", "tail": "amphotericin B"}, {"head": "mortality", "relation": "adverse effect", "tail": "amphotericin B"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : severe hypoglycaemia , mefloquine )",
"id": "23",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : severe hypoglycaemia , mefloquine )",
"output_json": "{\"relations\": [{\"head\": \"severe hypoglycaemia\", \"relation\": \"adverse effect\", \"tail\": \"mefloquine\"}]}",
"sentence": "Clinicians who manage cachectic patients , particularly those with protracted diarrhoea and/or receiving anti - malarial drugs including mefloquine , should be aware of the risk of severe hypoglycaemia ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : severe hypoglycaemia , mefloquine )
|
Option: adverse effect
|
{"relations": [{"head": "severe hypoglycaemia", "relation": "adverse effect", "tail": "mefloquine"}]}
|
( adverse effect : severe hypoglycaemia , mefloquine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nClinicians who manage cachectic patients , particularly those with protracted diarrhoea and/or receiving anti - malarial drugs including mefloquine , should be aware of the risk of severe hypoglycaemia .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "severe hypoglycaemia", "relation": "adverse effect", "tail": "mefloquine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : primary and secondary perforation of the bladder , epirubicin )",
"id": "24",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : primary and secondary perforation of the bladder , epirubicin )",
"output_json": "{\"relations\": [{\"head\": \"primary and secondary perforation of the bladder\", \"relation\": \"adverse effect\", \"tail\": \"epirubicin\"}]}",
"sentence": "MATERIALS AND METHODS : We present two cases of significant morbidity related to primary and secondary perforation of the bladder following two instillations of epirubicin ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : primary and secondary perforation of the bladder , epirubicin )
|
Option: adverse effect
|
{"relations": [{"head": "primary and secondary perforation of the bladder", "relation": "adverse effect", "tail": "epirubicin"}]}
|
( adverse effect : primary and secondary perforation of the bladder , epirubicin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nMATERIALS AND METHODS : We present two cases of significant morbidity related to primary and secondary perforation of the bladder following two instillations of epirubicin .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "primary and secondary perforation of the bladder", "relation": "adverse effect", "tail": "epirubicin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : nephropathy , Gold )",
"id": "25",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : nephropathy , Gold )",
"output_json": "{\"relations\": [{\"head\": \"nephropathy\", \"relation\": \"adverse effect\", \"tail\": \"Gold\"}]}",
"sentence": "Gold nephropathy : tissue analysis by X - ray fluorescent spectroscopy ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : nephropathy , Gold )
|
Option: adverse effect
|
{"relations": [{"head": "nephropathy", "relation": "adverse effect", "tail": "Gold"}]}
|
( adverse effect : nephropathy , Gold )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nGold nephropathy : tissue analysis by X - ray fluorescent spectroscopy .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "nephropathy", "relation": "adverse effect", "tail": "Gold"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : amnesia , Triazolam ) ; ( adverse effect : nocturnal bingeing , Triazolam )",
"id": "26",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : amnesia , Triazolam ) ; ( adverse effect : nocturnal bingeing , Triazolam )",
"output_json": "{\"relations\": [{\"head\": \"amnesia\", \"relation\": \"adverse effect\", \"tail\": \"Triazolam\"}, {\"head\": \"nocturnal bingeing\", \"relation\": \"adverse effect\", \"tail\": \"Triazolam\"}]}",
"sentence": "Triazolam - induced nocturnal bingeing with amnesia ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : amnesia , Triazolam ) ; ( adverse effect : nocturnal bingeing , Triazolam )
|
Option: adverse effect
|
{"relations": [{"head": "amnesia", "relation": "adverse effect", "tail": "Triazolam"}, {"head": "nocturnal bingeing", "relation": "adverse effect", "tail": "Triazolam"}]}
|
( adverse effect : amnesia , Triazolam ) ; ( adverse effect : nocturnal bingeing , Triazolam )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nTriazolam - induced nocturnal bingeing with amnesia .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "amnesia", "relation": "adverse effect", "tail": "Triazolam"}, {"head": "nocturnal bingeing", "relation": "adverse effect", "tail": "Triazolam"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : epiglottitis , prochlorperazine ) ; ( adverse effect : oro - pharyngeal dystonic reaction , prochlorperazine )",
"id": "27",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : epiglottitis , prochlorperazine ) ; ( adverse effect : oro - pharyngeal dystonic reaction , prochlorperazine )",
"output_json": "{\"relations\": [{\"head\": \"epiglottitis\", \"relation\": \"adverse effect\", \"tail\": \"prochlorperazine\"}, {\"head\": \"oro - pharyngeal dystonic reaction\", \"relation\": \"adverse effect\", \"tail\": \"prochlorperazine\"}]}",
"sentence": "This case presentation is of a patient who had the clinical appearance of epiglottitis , but actually had an oro - pharyngeal dystonic reaction to prochlorperazine ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : epiglottitis , prochlorperazine ) ; ( adverse effect : oro - pharyngeal dystonic reaction , prochlorperazine )
|
Option: adverse effect
|
{"relations": [{"head": "epiglottitis", "relation": "adverse effect", "tail": "prochlorperazine"}, {"head": "oro - pharyngeal dystonic reaction", "relation": "adverse effect", "tail": "prochlorperazine"}]}
|
( adverse effect : epiglottitis , prochlorperazine ) ; ( adverse effect : oro - pharyngeal dystonic reaction , prochlorperazine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThis case presentation is of a patient who had the clinical appearance of epiglottitis , but actually had an oro - pharyngeal dystonic reaction to prochlorperazine .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "epiglottitis", "relation": "adverse effect", "tail": "prochlorperazine"}, {"head": "oro - pharyngeal dystonic reaction", "relation": "adverse effect", "tail": "prochlorperazine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : proarrhythmic , amiodarone )",
"id": "28",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : proarrhythmic , amiodarone )",
"output_json": "{\"relations\": [{\"head\": \"proarrhythmic\", \"relation\": \"adverse effect\", \"tail\": \"amiodarone\"}]}",
"sentence": "The probable proarrhythmic action of amiodarone , although rare , is reviewed along with a discussion of the novel use of intravenous magnesium sulfate therapy ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : proarrhythmic , amiodarone )
|
Option: adverse effect
|
{"relations": [{"head": "proarrhythmic", "relation": "adverse effect", "tail": "amiodarone"}]}
|
( adverse effect : proarrhythmic , amiodarone )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThe probable proarrhythmic action of amiodarone , although rare , is reviewed along with a discussion of the novel use of intravenous magnesium sulfate therapy .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "proarrhythmic", "relation": "adverse effect", "tail": "amiodarone"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : abdominal right lower quadrant pain , cyclophosphamide ) ; ( adverse effect : cecal lymphoma , cyclophosphamide )",
"id": "29",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : abdominal right lower quadrant pain , cyclophosphamide ) ; ( adverse effect : cecal lymphoma , cyclophosphamide )",
"output_json": "{\"relations\": [{\"head\": \"abdominal right lower quadrant pain\", \"relation\": \"adverse effect\", \"tail\": \"cyclophosphamide\"}, {\"head\": \"cecal lymphoma\", \"relation\": \"adverse effect\", \"tail\": \"cyclophosphamide\"}]}",
"sentence": "Five and one - half years after the diagnosis of myeloma , while in remission on cyclophosphamide therapy , the patient experienced severe abdominal right lower quadrant pain due to a large cecal lymphoma ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : abdominal right lower quadrant pain , cyclophosphamide ) ; ( adverse effect : cecal lymphoma , cyclophosphamide )
|
Option: adverse effect
|
{"relations": [{"head": "abdominal right lower quadrant pain", "relation": "adverse effect", "tail": "cyclophosphamide"}, {"head": "cecal lymphoma", "relation": "adverse effect", "tail": "cyclophosphamide"}]}
|
( adverse effect : abdominal right lower quadrant pain , cyclophosphamide ) ; ( adverse effect : cecal lymphoma , cyclophosphamide )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nFive and one - half years after the diagnosis of myeloma , while in remission on cyclophosphamide therapy , the patient experienced severe abdominal right lower quadrant pain due to a large cecal lymphoma .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "abdominal right lower quadrant pain", "relation": "adverse effect", "tail": "cyclophosphamide"}, {"head": "cecal lymphoma", "relation": "adverse effect", "tail": "cyclophosphamide"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : cutaneous and hematologic toxicity , IL-2 )",
"id": "30",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : cutaneous and hematologic toxicity , IL-2 )",
"output_json": "{\"relations\": [{\"head\": \"cutaneous and hematologic toxicity\", \"relation\": \"adverse effect\", \"tail\": \"IL-2\"}]}",
"sentence": "OBJECTIVE : To report a case of cutaneous and hematologic toxicity in a patient treated with IL-2 ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : cutaneous and hematologic toxicity , IL-2 )
|
Option: adverse effect
|
{"relations": [{"head": "cutaneous and hematologic toxicity", "relation": "adverse effect", "tail": "IL-2"}]}
|
( adverse effect : cutaneous and hematologic toxicity , IL-2 )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nOBJECTIVE : To report a case of cutaneous and hematologic toxicity in a patient treated with IL-2 .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "cutaneous and hematologic toxicity", "relation": "adverse effect", "tail": "IL-2"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : lupus erythematosus , Sulfasalazine )",
"id": "31",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : lupus erythematosus , Sulfasalazine )",
"output_json": "{\"relations\": [{\"head\": \"lupus erythematosus\", \"relation\": \"adverse effect\", \"tail\": \"Sulfasalazine\"}]}",
"sentence": "Sulfasalazine - induced lupus erythematosus ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : lupus erythematosus , Sulfasalazine )
|
Option: adverse effect
|
{"relations": [{"head": "lupus erythematosus", "relation": "adverse effect", "tail": "Sulfasalazine"}]}
|
( adverse effect : lupus erythematosus , Sulfasalazine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nSulfasalazine - induced lupus erythematosus .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "lupus erythematosus", "relation": "adverse effect", "tail": "Sulfasalazine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Nephrotic syndrome , interferon - beta-1b )",
"id": "32",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Nephrotic syndrome , interferon - beta-1b )",
"output_json": "{\"relations\": [{\"head\": \"Nephrotic syndrome\", \"relation\": \"adverse effect\", \"tail\": \"interferon - beta-1b\"}]}",
"sentence": "Nephrotic syndrome associated with interferon - beta-1b therapy for multiple sclerosis ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Nephrotic syndrome , interferon - beta-1b )
|
Option: adverse effect
|
{"relations": [{"head": "Nephrotic syndrome", "relation": "adverse effect", "tail": "interferon - beta-1b"}]}
|
( adverse effect : Nephrotic syndrome , interferon - beta-1b )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nNephrotic syndrome associated with interferon - beta-1b therapy for multiple sclerosis .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Nephrotic syndrome", "relation": "adverse effect", "tail": "interferon - beta-1b"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : symptomatic methemoglobinemia , Depakote ) ; ( adverse effect : symptomatic methemoglobinemia , divalproex sodium )",
"id": "33",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : symptomatic methemoglobinemia , Depakote ) ; ( adverse effect : symptomatic methemoglobinemia , divalproex sodium )",
"output_json": "{\"relations\": [{\"head\": \"symptomatic methemoglobinemia\", \"relation\": \"adverse effect\", \"tail\": \"Depakote\"}, {\"head\": \"symptomatic methemoglobinemia\", \"relation\": \"adverse effect\", \"tail\": \"divalproex sodium\"}]}",
"sentence": "We report for the first time the development of symptomatic methemoglobinemia after an acute ingestion of divalproex sodium ( Depakote ) , resulting in serum concentrations 10 times greater than the therapeutic range ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : symptomatic methemoglobinemia , Depakote ) ; ( adverse effect : symptomatic methemoglobinemia , divalproex sodium )
|
Option: adverse effect
|
{"relations": [{"head": "symptomatic methemoglobinemia", "relation": "adverse effect", "tail": "Depakote"}, {"head": "symptomatic methemoglobinemia", "relation": "adverse effect", "tail": "divalproex sodium"}]}
|
( adverse effect : symptomatic methemoglobinemia , Depakote ) ; ( adverse effect : symptomatic methemoglobinemia , divalproex sodium )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nWe report for the first time the development of symptomatic methemoglobinemia after an acute ingestion of divalproex sodium ( Depakote ) , resulting in serum concentrations 10 times greater than the therapeutic range .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "symptomatic methemoglobinemia", "relation": "adverse effect", "tail": "Depakote"}, {"head": "symptomatic methemoglobinemia", "relation": "adverse effect", "tail": "divalproex sodium"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : dedifferentiation of the adipocytes , insulin ) ; ( adverse effect : hyperproduction of TNF - alpha , insulin )",
"id": "34",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : dedifferentiation of the adipocytes , insulin ) ; ( adverse effect : hyperproduction of TNF - alpha , insulin )",
"output_json": "{\"relations\": [{\"head\": \"dedifferentiation of the adipocytes\", \"relation\": \"adverse effect\", \"tail\": \"insulin\"}, {\"head\": \"hyperproduction of TNF - alpha\", \"relation\": \"adverse effect\", \"tail\": \"insulin\"}]}",
"sentence": "CONCLUSIONS : In our reported case , a local hyperproduction of TNF - alpha from macrophages that was induced by the injected insulin could explain the dedifferentiation of the adipocytes of the subcutaneous tissue and the reversion that was induced by the local injection of dexamethasone ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : dedifferentiation of the adipocytes , insulin ) ; ( adverse effect : hyperproduction of TNF - alpha , insulin )
|
Option: adverse effect
|
{"relations": [{"head": "dedifferentiation of the adipocytes", "relation": "adverse effect", "tail": "insulin"}, {"head": "hyperproduction of TNF - alpha", "relation": "adverse effect", "tail": "insulin"}]}
|
( adverse effect : dedifferentiation of the adipocytes , insulin ) ; ( adverse effect : hyperproduction of TNF - alpha , insulin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nCONCLUSIONS : In our reported case , a local hyperproduction of TNF - alpha from macrophages that was induced by the injected insulin could explain the dedifferentiation of the adipocytes of the subcutaneous tissue and the reversion that was induced by the local injection of dexamethasone .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "dedifferentiation of the adipocytes", "relation": "adverse effect", "tail": "insulin"}, {"head": "hyperproduction of TNF - alpha", "relation": "adverse effect", "tail": "insulin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Renal injury , anastrozole )",
"id": "35",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Renal injury , anastrozole )",
"output_json": "{\"relations\": [{\"head\": \"Renal injury\", \"relation\": \"adverse effect\", \"tail\": \"anastrozole\"}]}",
"sentence": "Renal injury due to anastrozole has not been published in the English literature ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Renal injury , anastrozole )
|
Option: adverse effect
|
{"relations": [{"head": "Renal injury", "relation": "adverse effect", "tail": "anastrozole"}]}
|
( adverse effect : Renal injury , anastrozole )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nRenal injury due to anastrozole has not been published in the English literature .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Renal injury", "relation": "adverse effect", "tail": "anastrozole"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : reversible granulocytopenia , procainamide )",
"id": "36",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : reversible granulocytopenia , procainamide )",
"output_json": "{\"relations\": [{\"head\": \"reversible granulocytopenia\", \"relation\": \"adverse effect\", \"tail\": \"procainamide\"}]}",
"sentence": "Sustained - release procainamide - induced reversible granulocytopenia after myocardial infarction ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : reversible granulocytopenia , procainamide )
|
Option: adverse effect
|
{"relations": [{"head": "reversible granulocytopenia", "relation": "adverse effect", "tail": "procainamide"}]}
|
( adverse effect : reversible granulocytopenia , procainamide )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nSustained - release procainamide - induced reversible granulocytopenia after myocardial infarction .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "reversible granulocytopenia", "relation": "adverse effect", "tail": "procainamide"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : ataxia , carbamazepine ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : dizziness , carbamazepine ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : drowsiness , carbamazepine ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : toxic symptoms , carbamazepine ) ; ( adverse effect : toxic symptoms , clarithromycin ) ; ( adverse effect : toxic symptoms , clarithromycin )",
"id": "37",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : ataxia , carbamazepine ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : dizziness , carbamazepine ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : drowsiness , carbamazepine ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : toxic symptoms , carbamazepine ) ; ( adverse effect : toxic symptoms , clarithromycin ) ; ( adverse effect : toxic symptoms , clarithromycin )",
"output_json": "{\"relations\": [{\"head\": \"ataxia\", \"relation\": \"adverse effect\", \"tail\": \"carbamazepine\"}, {\"head\": \"ataxia\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"ataxia\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"dizziness\", \"relation\": \"adverse effect\", \"tail\": \"carbamazepine\"}, {\"head\": \"dizziness\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"dizziness\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"drowsiness\", \"relation\": \"adverse effect\", \"tail\": \"carbamazepine\"}, {\"head\": \"drowsiness\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"drowsiness\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"toxic symptoms\", \"relation\": \"adverse effect\", \"tail\": \"carbamazepine\"}, {\"head\": \"toxic symptoms\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}, {\"head\": \"toxic symptoms\", \"relation\": \"adverse effect\", \"tail\": \"clarithromycin\"}]}",
"sentence": "During clarithromycin coadministration , four out of the seven patients developed moderate - to - severe toxic symptoms of carbamazepine , such as drowsiness , dizziness , and ataxia , which resolved within 5 days after clarithromycin discontinuation ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : ataxia , carbamazepine ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : dizziness , carbamazepine ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : drowsiness , carbamazepine ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : toxic symptoms , carbamazepine ) ; ( adverse effect : toxic symptoms , clarithromycin ) ; ( adverse effect : toxic symptoms , clarithromycin )
|
Option: adverse effect
|
{"relations": [{"head": "ataxia", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "ataxia", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "ataxia", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "dizziness", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "dizziness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "dizziness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "clarithromycin"}]}
|
( adverse effect : ataxia , carbamazepine ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : ataxia , clarithromycin ) ; ( adverse effect : dizziness , carbamazepine ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : dizziness , clarithromycin ) ; ( adverse effect : drowsiness , carbamazepine ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : drowsiness , clarithromycin ) ; ( adverse effect : toxic symptoms , carbamazepine ) ; ( adverse effect : toxic symptoms , clarithromycin ) ; ( adverse effect : toxic symptoms , clarithromycin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nDuring clarithromycin coadministration , four out of the seven patients developed moderate - to - severe toxic symptoms of carbamazepine , such as drowsiness , dizziness , and ataxia , which resolved within 5 days after clarithromycin discontinuation .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "ataxia", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "ataxia", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "ataxia", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "dizziness", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "dizziness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "dizziness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "drowsiness", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "carbamazepine"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "clarithromycin"}, {"head": "toxic symptoms", "relation": "adverse effect", "tail": "clarithromycin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : nephrotoxicity , cyclosporine )",
"id": "38",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : nephrotoxicity , cyclosporine )",
"output_json": "{\"relations\": [{\"head\": \"nephrotoxicity\", \"relation\": \"adverse effect\", \"tail\": \"cyclosporine\"}]}",
"sentence": "However , cyclosporine dependency is associated with the risk of nephrotoxicity ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : nephrotoxicity , cyclosporine )
|
Option: adverse effect
|
{"relations": [{"head": "nephrotoxicity", "relation": "adverse effect", "tail": "cyclosporine"}]}
|
( adverse effect : nephrotoxicity , cyclosporine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nHowever , cyclosporine dependency is associated with the risk of nephrotoxicity .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "nephrotoxicity", "relation": "adverse effect", "tail": "cyclosporine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : acute hemorrhagic gastritis , AZ ) ; ( adverse effect : AZ intoxication , AZ )",
"id": "39",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : acute hemorrhagic gastritis , AZ ) ; ( adverse effect : AZ intoxication , AZ )",
"output_json": "{\"relations\": [{\"head\": \"acute hemorrhagic gastritis\", \"relation\": \"adverse effect\", \"tail\": \"AZ\"}, {\"head\": \"AZ intoxication\", \"relation\": \"adverse effect\", \"tail\": \"AZ\"}]}",
"sentence": "We experienced a case of chronic renal failure in a patient suffering from acute hemorrhagic gastritis associated with AZ intoxication ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : acute hemorrhagic gastritis , AZ ) ; ( adverse effect : AZ intoxication , AZ )
|
Option: adverse effect
|
{"relations": [{"head": "acute hemorrhagic gastritis", "relation": "adverse effect", "tail": "AZ"}, {"head": "AZ intoxication", "relation": "adverse effect", "tail": "AZ"}]}
|
( adverse effect : acute hemorrhagic gastritis , AZ ) ; ( adverse effect : AZ intoxication , AZ )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nWe experienced a case of chronic renal failure in a patient suffering from acute hemorrhagic gastritis associated with AZ intoxication .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "acute hemorrhagic gastritis", "relation": "adverse effect", "tail": "AZ"}, {"head": "AZ intoxication", "relation": "adverse effect", "tail": "AZ"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : life - threatening complications , 5-FU )",
"id": "40",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : life - threatening complications , 5-FU )",
"output_json": "{\"relations\": [{\"head\": \"life - threatening complications\", \"relation\": \"adverse effect\", \"tail\": \"5-FU\"}]}",
"sentence": "We now report the first known cancer patient who developed life - threatening complications after treatment with topical 5-FU and was shown subsequently to have profound DPD deficiency ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : life - threatening complications , 5-FU )
|
Option: adverse effect
|
{"relations": [{"head": "life - threatening complications", "relation": "adverse effect", "tail": "5-FU"}]}
|
( adverse effect : life - threatening complications , 5-FU )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nWe now report the first known cancer patient who developed life - threatening complications after treatment with topical 5-FU and was shown subsequently to have profound DPD deficiency .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "life - threatening complications", "relation": "adverse effect", "tail": "5-FU"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : neurologic disease , penicillamine ) ; ( adverse effect : neurologic worsening , penicillamine )",
"id": "41",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : neurologic disease , penicillamine ) ; ( adverse effect : neurologic worsening , penicillamine )",
"output_json": "{\"relations\": [{\"head\": \"neurologic disease\", \"relation\": \"adverse effect\", \"tail\": \"penicillamine\"}, {\"head\": \"neurologic worsening\", \"relation\": \"adverse effect\", \"tail\": \"penicillamine\"}]}",
"sentence": "To develop information on the relative rarity or frequency of neurologic worsening with the initiation of penicillamine therapy , we conducted a retrospective survey of 25 additional patients with Wilson 's disease who met the criteria of presenting with neurologic disease and having been treated with penicillamine ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : neurologic disease , penicillamine ) ; ( adverse effect : neurologic worsening , penicillamine )
|
Option: adverse effect
|
{"relations": [{"head": "neurologic disease", "relation": "adverse effect", "tail": "penicillamine"}, {"head": "neurologic worsening", "relation": "adverse effect", "tail": "penicillamine"}]}
|
( adverse effect : neurologic disease , penicillamine ) ; ( adverse effect : neurologic worsening , penicillamine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nTo develop information on the relative rarity or frequency of neurologic worsening with the initiation of penicillamine therapy , we conducted a retrospective survey of 25 additional patients with Wilson 's disease who met the criteria of presenting with neurologic disease and having been treated with penicillamine .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "neurologic disease", "relation": "adverse effect", "tail": "penicillamine"}, {"head": "neurologic worsening", "relation": "adverse effect", "tail": "penicillamine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Vitamin K deficiency , Cephalosporins )",
"id": "42",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Vitamin K deficiency , Cephalosporins )",
"output_json": "{\"relations\": [{\"head\": \"Vitamin K deficiency\", \"relation\": \"adverse effect\", \"tail\": \"Cephalosporins\"}]}",
"sentence": "Cephalosporins are most likely associated with Vitamin K deficiency ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Vitamin K deficiency , Cephalosporins )
|
Option: adverse effect
|
{"relations": [{"head": "Vitamin K deficiency", "relation": "adverse effect", "tail": "Cephalosporins"}]}
|
( adverse effect : Vitamin K deficiency , Cephalosporins )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nCephalosporins are most likely associated with Vitamin K deficiency .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Vitamin K deficiency", "relation": "adverse effect", "tail": "Cephalosporins"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : Multiple seizures , bupropion )",
"id": "43",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : Multiple seizures , bupropion )",
"output_json": "{\"relations\": [{\"head\": \"Multiple seizures\", \"relation\": \"adverse effect\", \"tail\": \"bupropion\"}]}",
"sentence": "Multiple seizures after bupropion overdose in a small child ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : Multiple seizures , bupropion )
|
Option: adverse effect
|
{"relations": [{"head": "Multiple seizures", "relation": "adverse effect", "tail": "bupropion"}]}
|
( adverse effect : Multiple seizures , bupropion )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nMultiple seizures after bupropion overdose in a small child .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "Multiple seizures", "relation": "adverse effect", "tail": "bupropion"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : histological abnormalities of the glomerulus , IFN - beta )",
"id": "44",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : histological abnormalities of the glomerulus , IFN - beta )",
"output_json": "{\"relations\": [{\"head\": \"histological abnormalities of the glomerulus\", \"relation\": \"adverse effect\", \"tail\": \"IFN - beta\"}]}",
"sentence": "To our knowledge this is the first report that demonstrates histological abnormalities of the glomerulus associated with postoperative IFN - beta therapy for the malignant melanoma ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : histological abnormalities of the glomerulus , IFN - beta )
|
Option: adverse effect
|
{"relations": [{"head": "histological abnormalities of the glomerulus", "relation": "adverse effect", "tail": "IFN - beta"}]}
|
( adverse effect : histological abnormalities of the glomerulus , IFN - beta )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nTo our knowledge this is the first report that demonstrates histological abnormalities of the glomerulus associated with postoperative IFN - beta therapy for the malignant melanoma .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "histological abnormalities of the glomerulus", "relation": "adverse effect", "tail": "IFN - beta"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : hyperandrogenism , sodium valproate ) ; ( adverse effect : menstrual disorders , sodium valproate ) ; ( adverse effect : polycystic ovaries , sodium valproate ) ; ( adverse effect : Reproductive endocrine disorders , sodium valproate )",
"id": "45",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : hyperandrogenism , sodium valproate ) ; ( adverse effect : menstrual disorders , sodium valproate ) ; ( adverse effect : polycystic ovaries , sodium valproate ) ; ( adverse effect : Reproductive endocrine disorders , sodium valproate )",
"output_json": "{\"relations\": [{\"head\": \"hyperandrogenism\", \"relation\": \"adverse effect\", \"tail\": \"sodium valproate\"}, {\"head\": \"menstrual disorders\", \"relation\": \"adverse effect\", \"tail\": \"sodium valproate\"}, {\"head\": \"polycystic ovaries\", \"relation\": \"adverse effect\", \"tail\": \"sodium valproate\"}, {\"head\": \"Reproductive endocrine disorders\", \"relation\": \"adverse effect\", \"tail\": \"sodium valproate\"}]}",
"sentence": "BACKGROUND : Reproductive endocrine disorders characterized by menstrual disorders , polycystic ovaries , and hyperandrogenism seem to be common among women treated with sodium valproate for epilepsy ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : hyperandrogenism , sodium valproate ) ; ( adverse effect : menstrual disorders , sodium valproate ) ; ( adverse effect : polycystic ovaries , sodium valproate ) ; ( adverse effect : Reproductive endocrine disorders , sodium valproate )
|
Option: adverse effect
|
{"relations": [{"head": "hyperandrogenism", "relation": "adverse effect", "tail": "sodium valproate"}, {"head": "menstrual disorders", "relation": "adverse effect", "tail": "sodium valproate"}, {"head": "polycystic ovaries", "relation": "adverse effect", "tail": "sodium valproate"}, {"head": "Reproductive endocrine disorders", "relation": "adverse effect", "tail": "sodium valproate"}]}
|
( adverse effect : hyperandrogenism , sodium valproate ) ; ( adverse effect : menstrual disorders , sodium valproate ) ; ( adverse effect : polycystic ovaries , sodium valproate ) ; ( adverse effect : Reproductive endocrine disorders , sodium valproate )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nBACKGROUND : Reproductive endocrine disorders characterized by menstrual disorders , polycystic ovaries , and hyperandrogenism seem to be common among women treated with sodium valproate for epilepsy .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "hyperandrogenism", "relation": "adverse effect", "tail": "sodium valproate"}, {"head": "menstrual disorders", "relation": "adverse effect", "tail": "sodium valproate"}, {"head": "polycystic ovaries", "relation": "adverse effect", "tail": "sodium valproate"}, {"head": "Reproductive endocrine disorders", "relation": "adverse effect", "tail": "sodium valproate"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : neuropathic side effects , thalidomide )",
"id": "46",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : neuropathic side effects , thalidomide )",
"output_json": "{\"relations\": [{\"head\": \"neuropathic side effects\", \"relation\": \"adverse effect\", \"tail\": \"thalidomide\"}]}",
"sentence": "However , in order to avoid neuropathic side effects , patients under thalidomide therapy should be monitored every 6 months with nerve conduction studies while taking the drug ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : neuropathic side effects , thalidomide )
|
Option: adverse effect
|
{"relations": [{"head": "neuropathic side effects", "relation": "adverse effect", "tail": "thalidomide"}]}
|
( adverse effect : neuropathic side effects , thalidomide )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nHowever , in order to avoid neuropathic side effects , patients under thalidomide therapy should be monitored every 6 months with nerve conduction studies while taking the drug .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "neuropathic side effects", "relation": "adverse effect", "tail": "thalidomide"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : sub - acute neurotoxicity , methotrexate )",
"id": "47",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : sub - acute neurotoxicity , methotrexate )",
"output_json": "{\"relations\": [{\"head\": \"sub - acute neurotoxicity\", \"relation\": \"adverse effect\", \"tail\": \"methotrexate\"}]}",
"sentence": "Conventional and diffusion - weighted MRI findings of methotrexate related sub - acute neurotoxicity ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : sub - acute neurotoxicity , methotrexate )
|
Option: adverse effect
|
{"relations": [{"head": "sub - acute neurotoxicity", "relation": "adverse effect", "tail": "methotrexate"}]}
|
( adverse effect : sub - acute neurotoxicity , methotrexate )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nConventional and diffusion - weighted MRI findings of methotrexate related sub - acute neurotoxicity .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "sub - acute neurotoxicity", "relation": "adverse effect", "tail": "methotrexate"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : type 1 diabetes mellitus , recombinant alpha-2b peginterferon ) ; ( adverse effect : type 1 diabetes mellitus , ribavirin )",
"id": "48",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : type 1 diabetes mellitus , recombinant alpha-2b peginterferon ) ; ( adverse effect : type 1 diabetes mellitus , ribavirin )",
"output_json": "{\"relations\": [{\"head\": \"type 1 diabetes mellitus\", \"relation\": \"adverse effect\", \"tail\": \"recombinant alpha-2b peginterferon\"}, {\"head\": \"type 1 diabetes mellitus\", \"relation\": \"adverse effect\", \"tail\": \"ribavirin\"}]}",
"sentence": "The clinical course suggested that recombinant alpha-2b peginterferon plus ribavirin provoked type 1 diabetes mellitus , therefore , in patients who are candidates for interferon therapy the presence of pancreatic autoantibodies and the fasting plasma glucose level should be investigated before and during treatment ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : type 1 diabetes mellitus , recombinant alpha-2b peginterferon ) ; ( adverse effect : type 1 diabetes mellitus , ribavirin )
|
Option: adverse effect
|
{"relations": [{"head": "type 1 diabetes mellitus", "relation": "adverse effect", "tail": "recombinant alpha-2b peginterferon"}, {"head": "type 1 diabetes mellitus", "relation": "adverse effect", "tail": "ribavirin"}]}
|
( adverse effect : type 1 diabetes mellitus , recombinant alpha-2b peginterferon ) ; ( adverse effect : type 1 diabetes mellitus , ribavirin )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThe clinical course suggested that recombinant alpha-2b peginterferon plus ribavirin provoked type 1 diabetes mellitus , therefore , in patients who are candidates for interferon therapy the presence of pancreatic autoantibodies and the fasting plasma glucose level should be investigated before and during treatment .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "type 1 diabetes mellitus", "relation": "adverse effect", "tail": "recombinant alpha-2b peginterferon"}, {"head": "type 1 diabetes mellitus", "relation": "adverse effect", "tail": "ribavirin"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : anaphylactoid reaction , Gelofusine )",
"id": "49",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : anaphylactoid reaction , Gelofusine )",
"output_json": "{\"relations\": [{\"head\": \"anaphylactoid reaction\", \"relation\": \"adverse effect\", \"tail\": \"Gelofusine\"}]}",
"sentence": "A case of anaphylactoid reaction due solely to the use of Gelofusine in a patient with non - haemorrhagic hypovolaemia is presented , with a discussion on the management and the use of allergy identification jewellery ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : anaphylactoid reaction , Gelofusine )
|
Option: adverse effect
|
{"relations": [{"head": "anaphylactoid reaction", "relation": "adverse effect", "tail": "Gelofusine"}]}
|
( adverse effect : anaphylactoid reaction , Gelofusine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nA case of anaphylactoid reaction due solely to the use of Gelofusine in a patient with non - haemorrhagic hypovolaemia is presented , with a discussion on the management and the use of allergy identification jewellery .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "anaphylactoid reaction", "relation": "adverse effect", "tail": "Gelofusine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : nephrosis , interferon )",
"id": "50",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : nephrosis , interferon )",
"output_json": "{\"relations\": [{\"head\": \"nephrosis\", \"relation\": \"adverse effect\", \"tail\": \"interferon\"}]}",
"sentence": "SUBSEQUENT COURSE : The nephrosis resolved almost completely once the interferon was stopped and after immunosuppressive treatment ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : nephrosis , interferon )
|
Option: adverse effect
|
{"relations": [{"head": "nephrosis", "relation": "adverse effect", "tail": "interferon"}]}
|
( adverse effect : nephrosis , interferon )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nSUBSEQUENT COURSE : The nephrosis resolved almost completely once the interferon was stopped and after immunosuppressive treatment .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "nephrosis", "relation": "adverse effect", "tail": "interferon"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : CDI , lithium ) ; ( adverse effect : central diabetes insipidus , lithium )",
"id": "51",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : CDI , lithium ) ; ( adverse effect : central diabetes insipidus , lithium )",
"output_json": "{\"relations\": [{\"head\": \"CDI\", \"relation\": \"adverse effect\", \"tail\": \"lithium\"}, {\"head\": \"central diabetes insipidus\", \"relation\": \"adverse effect\", \"tail\": \"lithium\"}]}",
"sentence": "The association of central diabetes insipidus ( CDI ) with lithium use is rare ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : CDI , lithium ) ; ( adverse effect : central diabetes insipidus , lithium )
|
Option: adverse effect
|
{"relations": [{"head": "CDI", "relation": "adverse effect", "tail": "lithium"}, {"head": "central diabetes insipidus", "relation": "adverse effect", "tail": "lithium"}]}
|
( adverse effect : CDI , lithium ) ; ( adverse effect : central diabetes insipidus , lithium )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThe association of central diabetes insipidus ( CDI ) with lithium use is rare .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "CDI", "relation": "adverse effect", "tail": "lithium"}, {"head": "central diabetes insipidus", "relation": "adverse effect", "tail": "lithium"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : central nervous system depression , brimonidine )",
"id": "52",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : central nervous system depression , brimonidine )",
"output_json": "{\"relations\": [{\"head\": \"central nervous system depression\", \"relation\": \"adverse effect\", \"tail\": \"brimonidine\"}]}",
"sentence": "Apparent central nervous system depression in infants after the use of topical brimonidine ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : central nervous system depression , brimonidine )
|
Option: adverse effect
|
{"relations": [{"head": "central nervous system depression", "relation": "adverse effect", "tail": "brimonidine"}]}
|
( adverse effect : central nervous system depression , brimonidine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nApparent central nervous system depression in infants after the use of topical brimonidine .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "central nervous system depression", "relation": "adverse effect", "tail": "brimonidine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : ATIN , pranlukast ) ; ( adverse effect : ATIN , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast )",
"id": "53",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : ATIN , pranlukast ) ; ( adverse effect : ATIN , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast )",
"output_json": "{\"relations\": [{\"head\": \"ATIN\", \"relation\": \"adverse effect\", \"tail\": \"pranlukast\"}, {\"head\": \"ATIN\", \"relation\": \"adverse effect\", \"tail\": \"pranlukast\"}, {\"head\": \"hypersensitivity reaction\", \"relation\": \"adverse effect\", \"tail\": \"pranlukast\"}, {\"head\": \"hypersensitivity reaction\", \"relation\": \"adverse effect\", \"tail\": \"pranlukast\"}]}",
"sentence": "The case demonstrates that hypersensitivity reaction to pranlukast and resultant ATIN is possible , and that periodic urine testing in patients receiving pranlukast should be considered ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : ATIN , pranlukast ) ; ( adverse effect : ATIN , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast )
|
Option: adverse effect
|
{"relations": [{"head": "ATIN", "relation": "adverse effect", "tail": "pranlukast"}, {"head": "ATIN", "relation": "adverse effect", "tail": "pranlukast"}, {"head": "hypersensitivity reaction", "relation": "adverse effect", "tail": "pranlukast"}, {"head": "hypersensitivity reaction", "relation": "adverse effect", "tail": "pranlukast"}]}
|
( adverse effect : ATIN , pranlukast ) ; ( adverse effect : ATIN , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast ) ; ( adverse effect : hypersensitivity reaction , pranlukast )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThe case demonstrates that hypersensitivity reaction to pranlukast and resultant ATIN is possible , and that periodic urine testing in patients receiving pranlukast should be considered .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "ATIN", "relation": "adverse effect", "tail": "pranlukast"}, {"head": "ATIN", "relation": "adverse effect", "tail": "pranlukast"}, {"head": "hypersensitivity reaction", "relation": "adverse effect", "tail": "pranlukast"}, {"head": "hypersensitivity reaction", "relation": "adverse effect", "tail": "pranlukast"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : bilateral ptosis , vincristine )",
"id": "54",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : bilateral ptosis , vincristine )",
"output_json": "{\"relations\": [{\"head\": \"bilateral ptosis\", \"relation\": \"adverse effect\", \"tail\": \"vincristine\"}]}",
"sentence": "Five days after the fourth dose of vincristine , she presented with bilateral ptosis ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : bilateral ptosis , vincristine )
|
Option: adverse effect
|
{"relations": [{"head": "bilateral ptosis", "relation": "adverse effect", "tail": "vincristine"}]}
|
( adverse effect : bilateral ptosis , vincristine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nFive days after the fourth dose of vincristine , she presented with bilateral ptosis .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "bilateral ptosis", "relation": "adverse effect", "tail": "vincristine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : polyserositis , Clozapine )",
"id": "55",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : polyserositis , Clozapine )",
"output_json": "{\"relations\": [{\"head\": \"polyserositis\", \"relation\": \"adverse effect\", \"tail\": \"Clozapine\"}]}",
"sentence": "Clozapine induced polyserositis ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : polyserositis , Clozapine )
|
Option: adverse effect
|
{"relations": [{"head": "polyserositis", "relation": "adverse effect", "tail": "Clozapine"}]}
|
( adverse effect : polyserositis , Clozapine )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nClozapine induced polyserositis .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "polyserositis", "relation": "adverse effect", "tail": "Clozapine"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : flare - up , goserelin acetate ) ; ( adverse effect : severe dyspnea , goserelin acetate ) ; ( adverse effect : worsening pleuritis carcinomatosa , goserelin acetate )",
"id": "56",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : flare - up , goserelin acetate ) ; ( adverse effect : severe dyspnea , goserelin acetate ) ; ( adverse effect : worsening pleuritis carcinomatosa , goserelin acetate )",
"output_json": "{\"relations\": [{\"head\": \"flare - up\", \"relation\": \"adverse effect\", \"tail\": \"goserelin acetate\"}, {\"head\": \"severe dyspnea\", \"relation\": \"adverse effect\", \"tail\": \"goserelin acetate\"}, {\"head\": \"worsening pleuritis carcinomatosa\", \"relation\": \"adverse effect\", \"tail\": \"goserelin acetate\"}]}",
"sentence": "Four days after the initial injection of 3.6 mg of goserelin acetate , severe dyspnea developed due to worsening pleuritis carcinomatosa , which was considered as a flare - up ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : flare - up , goserelin acetate ) ; ( adverse effect : severe dyspnea , goserelin acetate ) ; ( adverse effect : worsening pleuritis carcinomatosa , goserelin acetate )
|
Option: adverse effect
|
{"relations": [{"head": "flare - up", "relation": "adverse effect", "tail": "goserelin acetate"}, {"head": "severe dyspnea", "relation": "adverse effect", "tail": "goserelin acetate"}, {"head": "worsening pleuritis carcinomatosa", "relation": "adverse effect", "tail": "goserelin acetate"}]}
|
( adverse effect : flare - up , goserelin acetate ) ; ( adverse effect : severe dyspnea , goserelin acetate ) ; ( adverse effect : worsening pleuritis carcinomatosa , goserelin acetate )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nFour days after the initial injection of 3.6 mg of goserelin acetate , severe dyspnea developed due to worsening pleuritis carcinomatosa , which was considered as a flare - up .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "flare - up", "relation": "adverse effect", "tail": "goserelin acetate"}, {"head": "severe dyspnea", "relation": "adverse effect", "tail": "goserelin acetate"}, {"head": "worsening pleuritis carcinomatosa", "relation": "adverse effect", "tail": "goserelin acetate"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : neutropenia , olanzapine ) ; ( adverse effect : neutropenia , thiazide )",
"id": "57",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : neutropenia , olanzapine ) ; ( adverse effect : neutropenia , thiazide )",
"output_json": "{\"relations\": [{\"head\": \"neutropenia\", \"relation\": \"adverse effect\", \"tail\": \"olanzapine\"}, {\"head\": \"neutropenia\", \"relation\": \"adverse effect\", \"tail\": \"thiazide\"}]}",
"sentence": "Second , we report a case of neutropenia , which proved to be fatal in a schizophrenia patient receiving olanzapine and thiazide ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : neutropenia , olanzapine ) ; ( adverse effect : neutropenia , thiazide )
|
Option: adverse effect
|
{"relations": [{"head": "neutropenia", "relation": "adverse effect", "tail": "olanzapine"}, {"head": "neutropenia", "relation": "adverse effect", "tail": "thiazide"}]}
|
( adverse effect : neutropenia , olanzapine ) ; ( adverse effect : neutropenia , thiazide )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nSecond , we report a case of neutropenia , which proved to be fatal in a schizophrenia patient receiving olanzapine and thiazide .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "neutropenia", "relation": "adverse effect", "tail": "olanzapine"}, {"head": "neutropenia", "relation": "adverse effect", "tail": "thiazide"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : squamous cell carcinoma , psoralens )",
"id": "58",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : squamous cell carcinoma , psoralens )",
"output_json": "{\"relations\": [{\"head\": \"squamous cell carcinoma\", \"relation\": \"adverse effect\", \"tail\": \"psoralens\"}]}",
"sentence": "In two patients with mycosis fungoides , a squamous cell carcinoma developed during therapy with psoralens plus long - wave ultraviolet radiation ( PUVA ) ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : squamous cell carcinoma , psoralens )
|
Option: adverse effect
|
{"relations": [{"head": "squamous cell carcinoma", "relation": "adverse effect", "tail": "psoralens"}]}
|
( adverse effect : squamous cell carcinoma , psoralens )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nIn two patients with mycosis fungoides , a squamous cell carcinoma developed during therapy with psoralens plus long - wave ultraviolet radiation ( PUVA ) .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "squamous cell carcinoma", "relation": "adverse effect", "tail": "psoralens"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : acute tubulointerstitial nephritis , Flurbiprofen )",
"id": "59",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : acute tubulointerstitial nephritis , Flurbiprofen )",
"output_json": "{\"relations\": [{\"head\": \"acute tubulointerstitial nephritis\", \"relation\": \"adverse effect\", \"tail\": \"Flurbiprofen\"}]}",
"sentence": "Flurbiprofen - associated acute tubulointerstitial nephritis ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : acute tubulointerstitial nephritis , Flurbiprofen )
|
Option: adverse effect
|
{"relations": [{"head": "acute tubulointerstitial nephritis", "relation": "adverse effect", "tail": "Flurbiprofen"}]}
|
( adverse effect : acute tubulointerstitial nephritis , Flurbiprofen )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nFlurbiprofen - associated acute tubulointerstitial nephritis .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "acute tubulointerstitial nephritis", "relation": "adverse effect", "tail": "Flurbiprofen"}]}
|
RE
|
ADE_corpus_sample_15000
|
train
|
[] |
{
"ground_truth": "( adverse effect : anaphylactoid reaction , zomepirac )",
"id": "60",
"instruction": "Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return \"None\". If only one relationship is found, format it as \"( relation1 : word1 , word2 )\". For multiple relationships, separate them with semicolons using the format: \"( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )\".\nOption: adverse effect \nText: {0} \nAnswer:",
"label": "( adverse effect : anaphylactoid reaction , zomepirac )",
"output_json": "{\"relations\": [{\"head\": \"anaphylactoid reaction\", \"relation\": \"adverse effect\", \"tail\": \"zomepirac\"}]}",
"sentence": "The mechanism of anaphylactoid reaction to zomepirac in this case , therefore , remains unclear ."
}
|
Identify and extract pairs of words along with their semantic relationship described in the text. If no valid relationship is found, return "None". If only one relationship is found, format it as "( relation1 : word1 , word2 )". For multiple relationships, separate them with semicolons using the format: "( relation1 : word1, word2 ) ; ( relation2 : word3 , word4 )".
|
( adverse effect : anaphylactoid reaction , zomepirac )
|
Option: adverse effect
|
{"relations": [{"head": "anaphylactoid reaction", "relation": "adverse effect", "tail": "zomepirac"}]}
|
( adverse effect : anaphylactoid reaction , zomepirac )
|
Extract all relationships between entities from the given text and return them in JSON format with the key "relations". The output should be a JSON string containing a list of objects, each with "head", "relation", and "tail".
|
[
{
"content": "You are an AI assistant specialized in RE tasks for the ADE_corpus_sample_15000 dataset. \nYour goal is to follow the instructions carefully and generate accurate outputs in JSON format.\nThe available options for this task are: adverse effect.",
"role": "system"
},
{
"content": "### Instruction:\nExtract all relationships between entities from the given text and return them in JSON format with the key \"relations\". The output should be a JSON string containing a list of objects, each with \"head\", \"relation\", and \"tail\".\n\n### Input:\nThe mechanism of anaphylactoid reaction to zomepirac in this case , therefore , remains unclear .\n\n### Output:",
"role": "user"
}
] |
{"relations": [{"head": "anaphylactoid reaction", "relation": "adverse effect", "tail": "zomepirac"}]}
|
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