README.md

metadata

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
• Dataset Structure
• 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
• Paper: CNER: Concept and Named Entity Recognition
• 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
• Paper: CNER: Concept and Named Entity Recognition
• 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:

{
    "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). Copyright of the dataset contents belongs to Babelscape.
• Citation Information:

@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, @framolfese and @sted97 for adding this dataset.