README.md

metadata

dataset_info:
  - config_name: corpus
    features:
      - name: _id
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 2740852
        num_examples: 5035
    download_size: 1772984
    dataset_size: 2740852
  - config_name: queries
    features:
      - name: _id
        dtype: string
      - name: text
        dtype: string
    splits:
      - name: train
        num_bytes: 3132
        num_examples: 50
    download_size: 3453
    dataset_size: 3132
  - config_name: relevance
    features:
      - name: query-id
        dtype: string
      - name: positive-corpus-ids
        sequence: string
      - name: bm25-ranked-ids
        sequence: string
    splits:
      - name: train
        num_bytes: 3388510
        num_examples: 50
    download_size: 442548
    dataset_size: 3388510
configs:
  - config_name: corpus
    data_files:
      - split: train
        path: corpus/train-*
  - config_name: queries
    data_files:
      - split: train
        path: queries/train-*
  - config_name: relevance
    data_files:
      - split: train
        path: relevance/train-*
language:
  - en
tags:
  - sentence-transformers
size_categories:
  - 1K<n<10K

NanoBEIR NQ with BM25 rankings

This dataset is an updated variant of NanoNQ, which is a subset of the NQ dataset from the Benchmark for Information Retrieval (BEIR). NQ was created as a subset of the rather large BEIR, designed to be more efficient to run. This dataset adds a bm25-ranked-ids column to the relevance subset, which contains a ranking of every single passage in the corpus to the query.

This dataset is used in Sentence Transformers for evaluating CrossEncoder (i.e. reranker) models on NanoBEIR by reranking the top k results from BM25.