NarrativeTime: Dense Temporal Annotation on a Timeline
Anna Rogers, Marzena Karpinska, Ankita Gupta, Vladislav Lialin, Gregory Smelkov, Anna Rumshisky
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.
BibTeX
@inproceedings{rogers-etal-2024-narrativetime,
title = "{N}arrative{T}ime: Dense Temporal Annotation on a Timeline",
author = "Rogers, Anna and
Karpinska, Marzena and
Gupta, Ankita and
Lialin, Vladislav and
Smelkov, Gregory and
Rumshisky, Anna",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1054/",
pages = "12053--12073"
}