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NarrativeTime: Dense Temporal Annotation on a Timeline

  • ,
  • Marzena Karpinska
    ,
  • Ankita Gupta
    ,
  • Vladislav Lialin
    ,
  • Gregory Smelkov
    ,
  • Anna Rumshisky
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 12053-12073 (21 pages)

Publication milestones

  • Published - 01/05/2024

Publication status

Published - 01/05/2024

Place of publication

Torino, Italia

Publisher

ELRA and ICCL

Publication IDs

  • Scopus: 85195912978

Host publication title

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Host publication editors

  • Nicoletta Calzolari
  • Min-Yen Kan
  • Veronique Hoste
  • Alessandro Lenci
  • Sakriani Sakti
  • Nianwen Xue

Abstract

For the past decade, temporal annotation has been sparse: only a small portion of event pairs in a text was annotated. We present NarrativeTime, the first timeline-based annotation framework that achieves full coverage of all possible TLINKs. To compare with the previous SOTA in dense temporal annotation, we perform full re-annotation of the classic TimeBankDense corpus (American English), which shows comparable agreement with a signigicant increase in density. We contribute TimeBankNT corpus (with each text fully annotated by two expert annotators), extensive annotation guidelines, open-source tools for annotation and conversion to TimeML format, and baseline results.

Publication metrics

PlumX

Citations
8

Access to documents

Final published version, 1.07 MB

Related Event

Title

Joint International Conference on Computational Linguistics, Language Resources and Evaluation

Event type

Conference

Degree of recognition

International event

Date

20/05/2024 - 25/05/2024

Location

TorinoItaly