beir-scifact / README.md
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metadata
license: apache-2.0
task_categories:
  - information-retrieval
  - text-retrieval
tags:
  - beir
  - scifact
  - information-retrieval
  - retrieval
  - search
configs:
  - config_name: corpus
    data_files:
      - split: train
        path: corpus/train-*
  - config_name: queries
    data_files:
      - split: train
        path: queries/train-*
dataset_info:
  - config_name: corpus
    features:
      - name: title
        dtype: string
      - name: metadata
        dtype: 'null'
      - name: text
        dtype: string
      - name: _id
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    splits:
      - name: train
        num_bytes: 7874970
        num_examples: 5183
    download_size: 4491413
    dataset_size: 7874970
  - config_name: queries
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      - name: _id
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    splits:
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        num_bytes: 2142892
        num_examples: 1109
    download_size: 1049977
    dataset_size: 2142892

BEIR SCIFACT Dataset (Migrated)

This is a migrated version of BeIR/scifact that is compatible with datasets library 4.0.0+.

Dataset Description

This dataset contains the scifact dataset from the BEIR benchmark, converted from the old script-based format to Parquet format.

Dataset Structure

Queries

  • Split 'queries': 1,109 examples

    • Features: ['_id', 'text', 'metadata']
  • Total examples: 1,109

Corpus

  • Split 'corpus': 5,183 examples

    • Features: ['_id', 'title', 'text', 'metadata']
  • Total examples: 5,183

Usage

from datasets import load_dataset

# Load queries (split: queries)
queries = load_dataset("Hyukkyu/beir-scifact", "queries", split="queries")

# Load corpus (split: corpus)
corpus = load_dataset("Hyukkyu/beir-scifact", "corpus", split="corpus")

Available Splits

Queries

  • queries: 1,109 examples

Corpus

  • corpus: 5,183 examples

Original Dataset

This dataset is migrated from: BeIR/scifact

Citation

If you use this dataset, please cite the original BEIR paper:

@article{thakur2021beir,
  title={BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
  author={Thakur, Nandan and Reimers, Nils and Ruckle, Andreas and Srivastava, Abhishek and Gurevych, Iryna},
  journal={arXiv preprint arXiv:2104.08663},
  year={2021}
}