Datasets:

langtech-innovation
/

trilingual_query_relevance

configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
dataset_info:
  features:
    - name: id
      dtype: string
    - name: query
      dtype: string
    - name: context
      dtype: string
    - name: lang
      dtype: string
    - name: relevance
      dtype: float64
  splits:
    - name: train
      num_bytes: 30262530
      num_examples: 61231
    - name: validation
      num_bytes: 7540711
      num_examples: 15348
  download_size: 26781939
  dataset_size: 37803241

Dataset Card for trilingual_query_relevance

This dataset is a query - context relevance correlation optimized for document retrieval in EN, CA and SP
Created from projecte_aina/RAG_Multilingual (train and validation splits, no test) and PaDaS-Lab/webfaq-retrieval datasets
It was created to fine tune embeddings models for use in Retrieval Augmented generation applications for these 3 languages
Context was limited to the previous and following sentences for the rellevant one where the original extractive factoid was located in the sources for the RAG_Multilingual dataset.
A 50% (approx) of the records were ranked as 1.0 relevant for the correct pairing of query-context
In the other 50% the queries and contexts were mixed up randomly (but in same language) and assigned 0.0 as a relevance.
Splits were 80% train and 20% validation

Dataset Details

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License: Apache 2.0

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Created to fine tune embeddings models for use in Retrieval Augmented generation applications

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