metadata

dataset_info:
  - config_name: corpus
    features:
      - name: _id
        dtype: string
      - name: title
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: corpus
        num_bytes: 11814444.868325485
        num_examples: 22933
    download_size: 6046630
    dataset_size: 11814444.868325485
  - config_name: default
    features:
      - name: query-id
        dtype: string
      - name: corpus-id
        dtype: string
      - name: score
        dtype: float64
    splits:
      - name: test
        num_bytes: 1110.7605332063795
        num_examples: 35
    download_size: 2196
    dataset_size: 1110.7605332063795
  - config_name: queries
    features:
      - name: _id
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: queries
        num_bytes: 1724.433371958285
        num_examples: 27
    download_size: 2922
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configs:
  - config_name: corpus
    data_files:
      - split: corpus
        path: corpus/corpus-*
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
  - config_name: queries
    data_files:
      - split: queries
        path: queries/queries-*
task_categories:
  - question-answering
language:
  - en
tags:
  - chemistry
  - wikipedia
  - nq
  - natural questions
  - chemteb
pretty_name: Chemical Natural Questions
size_categories:
  - 10K<n<100K
license: cc-by-nc-sa-4.0

Chemical Natural Questions

This dataset is created from the mteb/nq dataset on Hugging Face, which is part of the Natural Questions dataset containing real user questions issued to Google search, with answers sourced from Wikipedia. In this chemistry-specific subset, we filtered queries related to chemistry by starting from the chemistry category in Wikipedia and traversing up to three levels deep in linked articles. This approach allowed us to focus on chemistry-related queries, providing a targeted subset of the original dataset for domain-specific retrieval tasks.