Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
json
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
100K - 1M
Tags:
structure-prediction
License:
File size: 4,366 Bytes
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---
annotations_creators:
- machine-generated
- human-generated
language:
- en
license:
- cc-by-nc-sa-4.0
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: cner-dataset
tags:
- structure-prediction
size_categories:
- 100K<n<1M
---
## Table of Contents
- [Description](#description)
- [Dataset Structure](#dataset-structure)
- [Additional Information](#additional-information)
## Dataset Card for CNER dataset
## Dataset Description
- **Summary:** Concept and Named Entity Recognition (CNER) is a novel task that jointly handles the indentification and classification of concepts and named entities.
- **Repository:** [https://github.com/Babelscape/cner](https://github.com/Babelscape/cner)
- **Paper:** [CNER: Concept and Named Entity Recognition](https://aclanthology.org/2024.naacl-long.461/)
- **Point of Contact:** {martinelli, molfese, tedeschi, navigli}@diag.uniroma1.it
## Description
- **Summary:** Concept and Named Entity Recognition (CNER) is a novel task that jointly handles the indentification and classification of concepts and named entities.
- **Repository:** [https://github.com/Babelscape/cner](https://github.com/Babelscape/cner)
- **Paper:** [CNER: Concept and Named Entity Recognition](https://aclanthology.org/2024.naacl-long.461/)
- **Point of Contact:** {martinelli, molfese, tedeschi, navigli}@diag.uniroma1.it
## Dataset Structure
The data fields are the same among all splits.
- `tokens`: a `list` of `string` features.
- `pos`: a `list` of `string` features (Part-of-Speech tags).
- `c_vs_ne`: a `list` of `string` features identifying whether a token is a concept or a named entity.
- `cner_tags`: a `list` of cner classification labels (`str`).
- `cner_tags_ids`: a `list` of cner classification labels ids (`int`). Full tagset with indices:
```python
{
"O": 0,
"B-ANIMAL": 1,
"I-ANIMAL": 2,
"B-DISEASE": 3,
"I-DISEASE": 4,
"B-DISCIPLINE": 5,
"I-DISCIPLINE": 6,
"B-LANGUAGE": 7,
"I-LANGUAGE": 8,
"B-EVENT": 9,
"I-EVENT": 10,
"B-FOOD": 11,
"I-FOOD": 12,
"B-ARTIFACT": 13,
"I-ARTIFACT": 14,
"B-MEDIA": 15,
"I-MEDIA": 16,
"B-GROUP": 17,
"I-GROUP": 18,
"B-ORG": 19,
"I-ORG": 20,
"B-PER": 21,
"I-PER": 22,
"B-STRUCT": 23,
"I-STRUCT": 24,
"B-LOC": 25,
"I-LOC": 26,
"B-PLANT": 27,
"I-PLANT": 28,
"B-MONEY": 29,
"I-MONEY": 30,
"B-BIOLOGY": 31,
"I-BIOLOGY": 32,
"B-MEASURE": 33,
"I-MEASURE": 34,
"B-SUPER": 35,
"I-SUPER": 36,
"B-CELESTIAL": 37,
"I-CELESTIAL": 38,
"B-LAW": 39,
"I-LAW": 40,
"B-SUBSTANCE": 41,
"I-SUBSTANCE": 42,
"B-PART": 43,
"I-PART": 44,
"B-CULTURE": 45,
"I-CULTURE": 46,
"B-PROPERTY": 47,
"I-PROPERTY": 48,
"B-FEELING": 49,
"I-FEELING": 50,
"B-PSYCH": 51,
"I-PSYCH": 52,
"B-RELATION": 53,
"I-RELATION": 54,
"B-DATETIME": 55,
"I-DATETIME": 56,
"B-ASSET": 57,
"I-ASSET": 58
}
```
## Additional Information
- **Licensing Information**: Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). Copyright of the dataset contents belongs to Babelscape.
- **Citation Information**:
```bibtex
@inproceedings{martinelli-etal-2024-cner,
title = "{CNER}: Concept and Named Entity Recognition",
author = "Martinelli, Giuliano and
Molfese, Francesco and
Tedeschi, Simone and
Fern{\'a}ndez-Castro, Alberte and
Navigli, Roberto",
editor = "Duh, Kevin and
Gomez, Helena and
Bethard, Steven",
booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.naacl-long.461",
pages = "8329--8344"
}
```
- **Contributions**: Thanks to [@g185](https://github.com/g185), [@framolfese](https://github.com/framolfese) and [@sted97](https://github.com/sted97) for adding this dataset. |