---
license: cc0-1.0
configs:
- config_name: default
  data_files:
  - split: train
    path: train.jsonl
  - split: eval
    path: eval.jsonl
language:
- en
---

# Books Named Entity Recognition (NER) Dataset

A lightweight Named‑Entity‑Recognition (NER) corpus built from **titles and author names** contained in Project Gutenberg’s public catalogues.  It is intended for training or benchmarking entity extractors such as **Gliner** on bibliographic metadata.

---

## 1 Provenance
This dataset provenance originates from [**Project Gutenberg's public catalogue**](https://www.gutenberg.org/).

---

## 2  Quick facts

|                       |                               |
|-----------------------|-------------------------------|
| **Records (total)**   | 434 925 |
| **Train split**       | 391 432 queries |
| **Eval split**        | 43 493 queries |
| **Tokens / record**   |  6 – 30 (median ≈ 14) |
| **NER labels**        | `title`, `author` |
| **Source**            | `GUTINDEX.ALL` and yearly `GUTINDEX.20xx` files downloaded 18 April 2025 from `rsync://ftp.gutenberg.org` |
| **Language coverage** | English only |
| **License**           | **CC0 1.0 Public‑Domain Dedication** |

---

## 3  Dataset description

### 3.1  Origin of the data
* Project Gutenberg publishes yearly plain‑text catalogues (`GUTINDEX`) listing **eBook ID – Title – Author**.  These catalogues are public and do not contain the full texts.
* We parsed those files and turned each one into several **synthetic “user queries”** (patterns such as _“Looking for **[Title]** from **[Author]**.”_ or _“Any recommendations by **[Author]**?”_).

### 3.2  Fields
| Field | Type | Description |
|-------|------|-------------|
| `tokenized_text` | `List[str]` | The query tokens. |
| `ner` | `List[[int,int,str]]` | Spans in **token indices** (inclusive) and the label (`title` / `author`). |

Example:
```json
{
  "tokenized_text": [
    "Looking", "for", "La", "conqueste", "du", "chasteau", "d", "'", "amours", "conquestee", "par", "l", "'", "umilité", "du", "beau", "doulx", ",", "the", "title", "from", "Anonymous", "."
  ],
  "ner": [
    [2, 16, "title"],
    [21, 21, "author"]
  ]
}
```

### 3.3  Splits
The corpus is provided in two separate files:
* **train.jsonl** — 391 432 synthetic queries
* **eval.jsonl**  — 43 493 synthetic queries

---

## 4  How to load
```python
from datasets import load_dataset

ds_train = load_dataset("empathyai/books-ner-dataset", split="train")
ds_eval  = load_dataset("empathyai/books-ner-dataset", split="eval")
```

---

## 5  Licensing and legal basis (EU)

### 5.1  Why the data are in the public domain
1. **Factual nature** — Book titles and author names are mere facts.  Under EU law (CJEU *Infopaq* C‑5/08 and Art. 2 InfoSoc‑Directive 2001/29/EC) facts and very short expressions lacking originality are **not protected by copyright**.
2. **No sui generis database right** — The maker of Project Gutenberg’s catalogue is a U.S. entity; the EU database right (Directive 96/9/EC) only protects databases whose maker is **established in the EU**.

### 5.2  License chosen
To reflect the public‑domain status worldwide we apply the **Creative Commons CC0 1.0 Public‑Domain Dedication**.  You may copy, modify, distribute and use the dataset for any purpose without asking permission.

### 5.3  Trademarks and attribution
* “Project Gutenberg” is a registered trademark of the Project Gutenberg Literary Archive Foundation.  This dataset is **not** endorsed by or affiliated with PG.
* If you build on this dataset, please leave this disclaimer intact and do **not** use “Project Gutenberg” in a way that suggests endorsement.

---

## 6  Acknowledgements
Project Gutenberg volunteers for maintaining the free catalogue; HuggingFace for the dataset hosting.