README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
pretty_name: Named Temporal Expressions dataset
size_categories:
  - 100K<n<1M
source_datasets:
  - original
task_categories:
  - token-classification
task_ids: []

Dataset Card for named_timexes

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information

Dataset Description

• Homepage:
• Repository:
• Paper: https://aclanthology.org/R13-1015/
• Leaderboard:
• Point of Contact: Leon Derczynski

Dataset Summary

This is a dataset annotated for named temporal expression chunks.

The commonest temporal expressions typically contain date and time words, like April or hours. Research into recognising and interpreting these typical expressions is mature in many languages. However, there is a class of expressions that are less typical, very varied, and difficult to automatically interpret. These indicate dates and times, but are harder to detect because they often do not contain time words and are not used frequently enough to appear in conventional temporally-annotated corpora – for example Michaelmas or Vasant Panchami.

For more details see Recognising and Interpreting Named Temporal Expressions

Supported Tasks and Leaderboards

• Task: Named Entity Recognition (temporal expressions)

Languages

Englsih

Dataset Structure

Data Instances

Data Fields

Each tweet contains an ID, a list of tokens, and a list of timex chunk flags.

• id: a string feature.
• tokens: a list of strings .
• ntimex_tags: a list of class IDs (ints) for whether a token is out-of-timex or in a timex chunk.

  0: O
  1: T

Data Splits

Section	Token count
train	87 050
test	30 010

Dataset Creation

Curation Rationale

[Needs More Information]

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

[Needs More Information]

Annotations

Annotation process

[Needs More Information]

Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

[Needs More Information]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[Needs More Information]

Licensing Information

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation Information

@inproceedings{brucato-etal-2013-recognising,
    title = "Recognising and Interpreting Named Temporal Expressions",
    author = "Brucato, Matteo  and
      Derczynski, Leon  and
      Llorens, Hector  and
      Bontcheva, Kalina  and
      Jensen, Christian S.",
    booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing {RANLP} 2013",
    month = sep,
    year = "2013",
    address = "Hissar, Bulgaria",
    publisher = "INCOMA Ltd. Shoumen, BULGARIA",
    url = "https://aclanthology.org/R13-1015",
    pages = "113--121",
}

Contributions

Author-added dataset @leondz