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NarrativeTime: Dense Temporal Annotation on a Timeline

  • Anna Rogers
  • , Marzena Karpinska
  • , Ankita Gupta
  • , Vladislav Lialin
  • , Gregory Smelkov
  • , Anna Rumshisky
  • University of Massachusetts

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

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.
OriginalsprogEngelsk
TitelProceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
RedaktørerNicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Antal sider21
UdgivelsesstedTorino, Italia
ForlagELRA and ICCL
Publikationsdato1 maj 2024
Sider12053-12073
StatusUdgivet - 1 maj 2024
BegivenhedJoint International Conference on Computational Linguistics, Language Resources and Evaluation - Torino, Italien
Varighed: 20 maj 202425 maj 2024
https://aclanthology.org/2024.lrec-main.544/
https://aclanthology.org/2024.lrec-main.1054/

Konference

KonferenceJoint International Conference on Computational Linguistics, Language Resources and Evaluation
Land/OmrådeItalien
ByTorino
Periode20/05/202425/05/2024
Internetadresse

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