Reading the Manual: Event Extraction as Definition Comprehension

Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, Benjamin Van Durme


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.
Anthology ID:
2020.spnlp-1.9
Volume:
Proceedings of the Fourth Workshop on Structured Prediction for NLP
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | spnlp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
74–83
Language:
URL:
https://aclanthology.org/2020.spnlp-1.9
DOI:
10.18653/v1/2020.spnlp-1.9
Bibkey:
Cite (ACL):
Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, and Benjamin Van Durme. 2020. Reading the Manual: Event Extraction as Definition Comprehension. In Proceedings of the Fourth Workshop on Structured Prediction for NLP, pages 74–83, Online. Association for Computational Linguistics.
Cite (Informal):
Reading the Manual: Event Extraction as Definition Comprehension (Chen et al., spnlp 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.spnlp-1.9.pdf
Video:
 https://slideslive.com/38940159
Data
BioSQuAD