---
license: cc-by-4.0
language: ar
tags:
  - named-entity-recognition
  - arabic
  - human-annotated
  - iahlt
dataset_name: iahlt-ner-arabic
---

# IAHLT Named Entities Dataset (Arabic Subset)

**האיגוד הישראלי לטכנולוגיות שפת אנוש**  
**الرابطة الإسرائيلية لتكنولوجيا اللغة البشرية**  
**The Israeli Association of Human Language Technologies**  
https://www.iahlt.org

This dataset contains named entity annotations for Arabic texts from various sources, curated as part of the IAHLT multilingual NER project. The Arabic portion is provided here as a cleaned subset intended for training and evaluation in named entity recognition tasks.

## Files Included

This release includes the following JSONL files:

- `iahlt_ner_train.jsonl`
- `iahlt_ner_val.jsonl`
- `iahlt_ner_test.jsonl`

Each file contains one JSON object per line with the following fields:
- `text`: the raw paragraph text
- `label`: a list of triples `[start, end, label]` where:
  - `start` is the index of the first character of the entity
  - `end` is the index of the first character after the entity
  - `label` is the entity class (e.g., `PER`, `ORG`, etc.)
- `metadata`: a dictionary with source and annotation metadata

## Entity Types

The dataset includes the following entity types (summed across splits):

| Entity    | Count |
|-----------|-------|
| GPE       | 26,767 |
| PER       | 22,694 |
| ORG       | 19,906 |
| TIMEX     | 10,288 |
| TTL       | 10,075 |
| FAC       | 4,740 |
| MISC      | 7,087 |
| LOC       | 5,389 |
| EVE       | 2,595 |
| WOA       | 1,781 |
| DUC       | 1,715 |
| ANG       |   732 |
| INFORMAL  |    10 |

> Note: These statistics reflect a cleaned version of the dataset. Some entities and texts have been modified or removed for consistency and usability.

## Annotation Notes

- Entity spans were manually annotated at the grapheme level and then normalized using Arabic-specific punctuation and spacing rules.
- Nested spans are allowed.
- The dataset was cleaned to ensure compatibility with common NER training formats.

## License

This dataset is released under the [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) license.

## Acknowledgments

We thank all annotators and contributors who worked on this corpus.