DinoStackAI/narrativeqa-rag

NarrativeQA RAG

Dataset for Retrieval-Augmented Generation (RAG) based on NarrativeQA.

Structure

Subset	Splits	Description
corpus	train (default)	Wikipedia plot summaries shared across all query splits
queries	train, dev, test	Reading comprehension questions
qrels	train, dev, test	Relevance judgments (query ↔ document)
answers	train, dev, test	Reference answers (longest annotated answer)

Dataset statistics

Split	Queries	Corpus
train	32747	1572
dev	3461	1572
test	10557	1572

The corpus is shared across all splits and contains Wikipedia plot summaries (document.summary.text) from the original NarrativeQA documents.

• Dev split: mapped from the original validation split
• Corpus source: unique documents from train, validation and test splits

Source

Component	NarrativeQA resource
Train	train split from deepmind/narrativeqa
Dev	validation split
Test	test split
Corpus	document.summary.text (+ document.summary.title)
Answers	Longest answer text per question

Schema

corpus

{"id": "...", "title": "...", "text": "..."}

queries

{"id": "...", "text": "..."}

qrels

{"query_id": "...", "corpus_id": "...", "score": 1}

answers

{"query_id": "...", "answer": "..."}

Usage

from datasets import load_dataset

corpus = load_dataset("DinoStackAI/narrativeqa-rag", "corpus")["train"]
queries = load_dataset("DinoStackAI/narrativeqa-rag", "queries")
qrels = load_dataset("DinoStackAI/narrativeqa-rag", "qrels")
answers = load_dataset("DinoStackAI/narrativeqa-rag", "answers")

train_queries = queries["train"]
dev_qrels = qrels["dev"]
test_answers = answers["test"]

Citation

NarrativeQA is released under the Apache 2.0 License.

@article{kocisky-etal-2018-narrativeqa,
    title = "The {N}arrative{QA} Reading Comprehension Challenge",
    author = "Ko{\v{c}}isk{\'y}, Tom{\'a}{\v{s}}  and
      Schwarz, Jonathan  and
      Blunsom, Phil  and
      Dyer, Chris  and
      Hermann, Karl Moritz  and
      Melis, G{\'a}bor  and
      Grefenstette, Edward",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "6",
    year = "2018",
    pages = "317--328",
}