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NarrativeTime: Dense Temporal Annotation on a Timeline

  • ,
  • Marzena Karpinska
    ,
  • Ankita Gupta
    ,
  • Vladislav Lialin
    ,
  • Gregory Smelkov
    ,
  • Anna Rumshisky
  • University of Massachusetts
Research Output:
Other contribution
Other contribution

Publication Information

Output type

Research Output:
Other contribution
Other contribution

Original language

English

Publication milestones

  • Published - 22/12/2022

Publication status

Published - 22/12/2022

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 TimeBankDense corpus, which shows comparable agreement with a significant 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, baseline results, as well as quantitative and qualitative analysis of inter-annotator agreement.