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--- |
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pretty_name: KoBEST |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- expert-generated |
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language: |
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- ko |
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license: |
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- cc-by-sa-4.0 |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- original |
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configs: |
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- config_name: boolq |
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data_files: |
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- split: train |
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path: "boolq/train.jsonl" |
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- split: test |
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path: "boolq/test.jsonl" |
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- split: validation |
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path: "boolq/validation.jsonl" |
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- config_name: copa |
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data_files: |
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- split: train |
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path: "copa/train.jsonl" |
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- split: test |
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path: "copa/test.jsonl" |
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- split: validation |
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path: "copa/validation.jsonl" |
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- config_name: hellaswag |
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data_files: |
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- split: train |
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path: "hellaswag/train.jsonl" |
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- split: test |
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path: "hellaswag/test.jsonl" |
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- split: validation |
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path: "hellaswag/validation.jsonl" |
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- config_name: sentineg |
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data_files: |
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- split: train |
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path: "sentineg/train.jsonl" |
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- split: test |
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path: "sentineg/test.jsonl" |
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- split: test_originated |
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path: "sentineg/test_originated.jsonl" |
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- split: validation |
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path: "sentineg/validation.jsonl" |
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- config_name: wic |
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data_files: |
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- split: train |
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path: "wic/train.jsonl" |
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- split: test |
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path: "wic/test.jsonl" |
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- split: validation |
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path: "wic/validation.jsonl" |
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--- |
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# Dataset Card for KoBEST |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Repository:** https://github.com/SKT-LSL/KoBEST_datarepo |
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- **Paper:** |
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- **Point of Contact:** https://github.com/SKT-LSL/KoBEST_datarepo/issues |
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### Dataset Summary |
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KoBEST is a Korean benchmark suite consists of 5 natural language understanding tasks that requires advanced knowledge in Korean. |
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### Supported Tasks and Leaderboards |
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Boolean Question Answering, Choice of Plausible Alternatives, Words-in-Context, HellaSwag, Sentiment Negation Recognition |
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### Languages |
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`ko-KR` |
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## Dataset Structure |
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### Data Instances |
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#### KB-BoolQ |
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An example of a data point looks as follows. |
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``` |
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{'paragraph': '두아 리파(Dua Lipa, 1995년 8월 22일 ~ )는 잉글랜드의 싱어송라이터, 모델이다. BBC 사운드 오브 2016 명단에 노미닛되었다. 싱글 "Be the One"가 영국 싱글 차트 9위까지 오르는 등 성과를 보여주었다.', |
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'question': '두아 리파는 영국인인가?', |
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'label': 1} |
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``` |
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#### KB-COPA |
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An example of a data point looks as follows. |
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``` |
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{'premise': '물을 오래 끓였다.', |
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'question': '결과', |
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'alternative_1': '물의 양이 늘어났다.', |
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'alternative_2': '물의 양이 줄어들었다.', |
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'label': 1} |
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``` |
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#### KB-WiC |
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An example of a data point looks as follows. |
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``` |
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{'word': '양분', |
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'context_1': '토양에 [양분]이 풍부하여 나무가 잘 자란다. ', |
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'context_2': '태아는 모체로부터 [양분]과 산소를 공급받게 된다.', |
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'label': 1} |
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``` |
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#### KB-HellaSwag |
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An example of a data point looks as follows. |
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``` |
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{'context': '모자를 쓴 투수가 타자에게 온 힘을 다해 공을 던진다. 공이 타자에게 빠른 속도로 다가온다. 타자가 공을 배트로 친다. 배트에서 깡 소리가 난다. 공이 하늘 위로 날아간다.', |
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'ending_1': '외야수가 떨어지는 공을 글러브로 잡는다.', |
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'ending_2': '외야수가 공이 떨어질 위치에 자리를 잡는다.', |
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'ending_3': '심판이 아웃을 외친다.', |
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'ending_4': '외야수가 공을 따라 뛰기 시작한다.', |
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'label': 3} |
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``` |
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#### KB-SentiNeg |
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An example of a data point looks as follows. |
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``` |
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{'sentence': '택배사 정말 마음에 듬', |
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'label': 1} |
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``` |
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### Data Fields |
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### KB-BoolQ |
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+ `paragraph`: a `string` feature |
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+ `question`: a `string` feature |
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+ `label`: a classification label, with possible values `False`(0) and `True`(1) |
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### KB-COPA |
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+ `premise`: a `string` feature |
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+ `question`: a `string` feature |
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+ `alternative_1`: a `string` feature |
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+ `alternative_2`: a `string` feature |
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+ `label`: an answer candidate label, with possible values `alternative_1`(0) and `alternative_2`(1) |
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### KB-WiC |
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+ `target_word`: a `string` feature |
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+ `context_1`: a `string` feature |
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+ `context_2`: a `string` feature |
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+ `label`: a classification label, with possible values `False`(0) and `True`(1) |
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### KB-HellaSwag |
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+ `target_word`: a `string` feature |
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+ `context_1`: a `string` feature |
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+ `context_2`: a `string` feature |
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+ `label`: a classification label, with possible values `False`(0) and `True`(1) |
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### KB-SentiNeg |
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+ `sentence`: a `string` feature |
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+ `label`: a classification label, with possible values `Negative`(0) and `Positive`(1) |
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### Data Splits |
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#### KB-BoolQ |
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+ train: 3,665 |
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+ dev: 700 |
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+ test: 1,404 |
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#### KB-COPA |
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+ train: 3,076 |
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+ dev: 1,000 |
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+ test: 1,000 |
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#### KB-WiC |
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+ train: 3,318 |
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+ dev: 1,260 |
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+ test: 1,260 |
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#### KB-HellaSwag |
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+ train: 3,665 |
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+ dev: 700 |
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+ test: 1,404 |
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#### KB-SentiNeg |
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+ train: 3,649 |
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+ dev: 400 |
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+ test: 397 |
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+ test_originated: 397 (Corresponding training data where the test set is originated from.) |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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### Personal and Sensitive Information |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[More Information Needed] |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Licensing Information |
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``` |
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@misc{https://doi.org/10.48550/arxiv.2204.04541, |
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doi = {10.48550/ARXIV.2204.04541}, |
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url = {https://arxiv.org/abs/2204.04541}, |
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author = {Kim, Dohyeong and Jang, Myeongjun and Kwon, Deuk Sin and Davis, Eric}, |
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title = {KOBEST: Korean Balanced Evaluation of Significant Tasks}, |
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publisher = {arXiv}, |
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year = {2022}, |
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} |
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``` |
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[More Information Needed] |
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### Contributions |
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Thanks to [@MJ-Jang](https://github.com/MJ-Jang) for adding this dataset. |
