@inproceedings{ma-etal-2021-eventplus,
title = "{E}vent{P}lus: A Temporal Event Understanding Pipeline",
author = "Ma, Mingyu Derek and
Sun, Jiao and
Yang, Mu and
Huang, Kung-Hsiang and
Wen, Nuan and
Singh, Shikhar and
Han, Rujun and
Peng, Nanyun",
editor = "Sil, Avi and
Lin, Xi Victoria",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-demos.7",
doi = "10.18653/v1/2021.naacl-demos.7",
pages = "56--65",
abstract = "We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, event argument detection, event duration and temporal relation extraction. Event information, especially event temporal knowledge, is a type of common sense knowledge that helps people understand how stories evolve and provides predictive hints for future events. EventPlus as the first comprehensive temporal event understanding pipeline provides a convenient tool for users to quickly obtain annotations about events and their temporal information for any user-provided document. Furthermore, we show EventPlus can be easily adapted to other domains (e.g., biomedical domain). We make EventPlus publicly available to facilitate event-related information extraction and downstream applications.",
}
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<abstract>We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, event argument detection, event duration and temporal relation extraction. Event information, especially event temporal knowledge, is a type of common sense knowledge that helps people understand how stories evolve and provides predictive hints for future events. EventPlus as the first comprehensive temporal event understanding pipeline provides a convenient tool for users to quickly obtain annotations about events and their temporal information for any user-provided document. Furthermore, we show EventPlus can be easily adapted to other domains (e.g., biomedical domain). We make EventPlus publicly available to facilitate event-related information extraction and downstream applications.</abstract>
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%0 Conference Proceedings
%T EventPlus: A Temporal Event Understanding Pipeline
%A Ma, Mingyu Derek
%A Sun, Jiao
%A Yang, Mu
%A Huang, Kung-Hsiang
%A Wen, Nuan
%A Singh, Shikhar
%A Han, Rujun
%A Peng, Nanyun
%Y Sil, Avi
%Y Lin, Xi Victoria
%S Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F ma-etal-2021-eventplus
%X We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, event argument detection, event duration and temporal relation extraction. Event information, especially event temporal knowledge, is a type of common sense knowledge that helps people understand how stories evolve and provides predictive hints for future events. EventPlus as the first comprehensive temporal event understanding pipeline provides a convenient tool for users to quickly obtain annotations about events and their temporal information for any user-provided document. Furthermore, we show EventPlus can be easily adapted to other domains (e.g., biomedical domain). We make EventPlus publicly available to facilitate event-related information extraction and downstream applications.
%R 10.18653/v1/2021.naacl-demos.7
%U https://aclanthology.org/2021.naacl-demos.7
%U https://doi.org/10.18653/v1/2021.naacl-demos.7
%P 56-65
Markdown (Informal)
[EventPlus: A Temporal Event Understanding Pipeline](https://aclanthology.org/2021.naacl-demos.7) (Ma et al., NAACL 2021)
ACL
- Mingyu Derek Ma, Jiao Sun, Mu Yang, Kung-Hsiang Huang, Nuan Wen, Shikhar Singh, Rujun Han, and Nanyun Peng. 2021. EventPlus: A Temporal Event Understanding Pipeline. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations, pages 56–65, Online. Association for Computational Linguistics.