@inproceedings{chen-etal-2020-reading,
title = "Reading the Manual: Event Extraction as Definition Comprehension",
author = "Chen, Yunmo and
Chen, Tongfei and
Ebner, Seth and
White, Aaron Steven and
Van Durme, Benjamin",
editor = "Agrawal, Priyanka and
Kozareva, Zornitsa and
Kreutzer, Julia and
Lampouras, Gerasimos and
Martins, Andr{\'e} and
Ravi, Sujith and
Vlachos, Andreas",
booktitle = "Proceedings of the Fourth Workshop on Structured Prediction for NLP",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.spnlp-1.9",
doi = "10.18653/v1/2020.spnlp-1.9",
pages = "74--83",
abstract = "We ask whether text understanding has progressed to where we may extract event information through incremental refinement of bleached statements derived from annotation manuals. Such a capability would allow for the trivial construction and extension of an extraction framework by intended end-users through declarations such as, {``}Some person was born in some location at some time.{''} We introduce an example of a model that employs such statements, with experiments illustrating we can extract events under closed ontologies and generalize to unseen event types simply by reading new definitions.",
}
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%0 Conference Proceedings
%T Reading the Manual: Event Extraction as Definition Comprehension
%A Chen, Yunmo
%A Chen, Tongfei
%A Ebner, Seth
%A White, Aaron Steven
%A Van Durme, Benjamin
%Y Agrawal, Priyanka
%Y Kozareva, Zornitsa
%Y Kreutzer, Julia
%Y Lampouras, Gerasimos
%Y Martins, André
%Y Ravi, Sujith
%Y Vlachos, Andreas
%S Proceedings of the Fourth Workshop on Structured Prediction for NLP
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F chen-etal-2020-reading
%X We ask whether text understanding has progressed to where we may extract event information through incremental refinement of bleached statements derived from annotation manuals. Such a capability would allow for the trivial construction and extension of an extraction framework by intended end-users through declarations such as, “Some person was born in some location at some time.” We introduce an example of a model that employs such statements, with experiments illustrating we can extract events under closed ontologies and generalize to unseen event types simply by reading new definitions.
%R 10.18653/v1/2020.spnlp-1.9
%U https://aclanthology.org/2020.spnlp-1.9
%U https://doi.org/10.18653/v1/2020.spnlp-1.9
%P 74-83
Markdown (Informal)
[Reading the Manual: Event Extraction as Definition Comprehension](https://aclanthology.org/2020.spnlp-1.9) (Chen et al., spnlp 2020)
ACL