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Datasets:
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kilt

Tasks:
Text Retrieval
Modalities:
Text
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parquet
Languages:
English
Size:
100M - 1B
Tags:
wikipedia
kilt
retrieval
en
paragraph
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metadata 
language:
  - en
license: cc-by-sa-4.0
pretty_name: KILT Wikipedia knowledge source (paragraph-level)
tags:
  - wikipedia
  - kilt
  - retrieval
  - en
  - paragraph
task_categories:
  - text-retrieval

KILT Wikipedia — paragraph-level (flattened)

Dataset summary

This dataset is a flattened view of the KILT knowledge source (kilt_knowledgesource.json): each row is one Wikipedia paragraph (one string in the original per-page text list), not one page per row.

  • Source corpus: KILT Wikipedia knowledge source (2019/08/01 Wikipedia dump, per KILT README).
  • Split: train only (full paragraph stream).
  • Rows (train): 111,789,997
  • Input shards used: 112 JSONL file(s) (part-*.jsonl).
  • Parquet chunks before Hub push: 2236 (batch_rows=50000, Hub max_shard_size=500MB).

Data fields

Column Type Description
wikipedia_id string KILT Wikipedia page id
wikipedia_title string Page title
text string Single paragraph body
_id string Stable id: {<page _id>}::p{<paragraph_index>}

How it was built

  1. Convert kilt_knowledgesource.json (JSONL, one JSON object per line) with OSCAR_like_experiments/scripts/convert_kilt_knowledge_source_to_paragraph_jsonl.py.
  2. Upload with OSCAR_like_experiments/scripts/push_kilt_paragraph_jsonl_to_hub.py from directory: /home/jovyan/rpt/OSCAR_like_experiments/scripts/kilt_knowledgesource.

Intended use

Sparse / dense retrieval indexing (e.g. BM25, SPLADE) where each document unit is a paragraph, matching the KILT-style chunking used in RAG pipelines.

Limitations

  • Text is English Wikipedia as packaged in KILT; formatting/markup follows KILT preprocessing.
  • Not an official Meta/Facebook dataset release; this is a derived redistribution — comply with Wikipedia and KILT terms.

Citation

Please cite KILT (and Wikipedia as appropriate):

@inproceedings{petroni-etal-2021-kilt,
  title = {KILT}: a Benchmark for Knowledge Intensive Language Tasks,
  author = {Petroni, Fabio and Piktus, Aleksandra and Fan, Angela and others},
  booktitle = {NAACL-HLT},
  year = {2021},
}

Repository: facebookresearch/KILT

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Dataset repo: s-nlp/kilt