README.md

---
license: apache-2.0
task_categories:
- question-answering
- text-retrieval
language:
- en
tags:
- rag
- narrativeqa
- reading-comprehension
- retrieval
size_categories:
- 10K<n<100K
configs:
- config_name: answers
  data_files:
  - split: train
    path: answers/train*
  - split: dev
    path: answers/dev*
  - split: test
    path: answers/test*
- config_name: corpus
  data_files:
  - split: train
    path: corpus/*
- config_name: qrels
  data_files:
  - split: train
    path: qrels/train*
  - split: dev
    path: qrels/dev*
  - split: test
    path: qrels/test*
- config_name: queries
  data_files:
  - split: train
    path: queries/train*
  - split: dev
    path: queries/dev*
  - split: test
    path: queries/test*
- config_name: retrieved_docs
  data_files:
  - split: train
    path: retrieved_docs/train-*
  - split: dev
    path: retrieved_docs/dev-*
  - split: test
    path: retrieved_docs/test-*
dataset_info:
  config_name: retrieved_docs
  features:
  - name: query_id
    dtype: string
  - name: corpus_id
    dtype: string
  - name: rank
    dtype: int64
  - name: retrieval_score
    dtype: float64
  - name: is_relevant
    dtype: bool
  splits:
  - name: train
    num_bytes: 37045044
    num_examples: 327470
  - name: dev
    num_bytes: 3915257
    num_examples: 34610
  - name: test
    num_bytes: 11942607
    num_examples: 105570
  download_size: 6206098
  dataset_size: 52902908
---

# NarrativeQA RAG

Dataset for Retrieval-Augmented Generation (RAG) based on [NarrativeQA](https://huggingface.co/datasets/deepmind/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](https://huggingface.co/datasets/deepmind/narrativeqa) |
| Dev | `validation` split |
| Test | `test` split |
| Corpus | `document.summary.text` (+ `document.summary.title`) |
| Answers | Longest answer text per question |

## Schema

### corpus
```json
{"id": "...", "title": "...", "text": "..."}
```

### queries
```json
{"id": "...", "text": "..."}
```

### qrels
```json
{"query_id": "...", "corpus_id": "...", "score": 1}
```

### answers
```json
{"query_id": "...", "answer": "..."}
```

## Usage

```python
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](https://www.apache.org/licenses/LICENSE-2.0).

```bibtex
@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",
}
```