TY - GEN
T1 - Zero-shot Event Extraction via Transfer Learning
T2 - Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021
AU - Lyu, Qing
AU - Zhang, Hongming
AU - Sulem, Elior
AU - Roth, Dan
N1 - Publisher Copyright: © 2021 Association for Computational Linguistics.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Event extraction has long been a challenging task, addressed mostly with supervised methods that require expensive annotation and are not extensible to new event ontologies. In this work, we explore the possibility of zeroshot event extraction by formulating it as a set of Textual Entailment (TE) and/or Question Answering (QA) queries (e.g. "A city was attacked"entails "There is an attack"), exploiting pretrained TE/QA models for direct transfer. On ACE-2005 and ERE, our system achieves acceptable results, yet there is still a large gap from supervised approaches, showing that current QA and TE technologies fail in transferring to a different domain. To investigate the reasons behind the gap, we analyze the remaining key challenges, their respective impact, and possible improvement directions.
AB - Event extraction has long been a challenging task, addressed mostly with supervised methods that require expensive annotation and are not extensible to new event ontologies. In this work, we explore the possibility of zeroshot event extraction by formulating it as a set of Textual Entailment (TE) and/or Question Answering (QA) queries (e.g. "A city was attacked"entails "There is an attack"), exploiting pretrained TE/QA models for direct transfer. On ACE-2005 and ERE, our system achieves acceptable results, yet there is still a large gap from supervised approaches, showing that current QA and TE technologies fail in transferring to a different domain. To investigate the reasons behind the gap, we analyze the remaining key challenges, their respective impact, and possible improvement directions.
UR - http://www.scopus.com/inward/record.url?scp=85119156721&partnerID=8YFLogxK
M3 - Conference contribution
T3 - ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference
SP - 322
EP - 332
BT - ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference
PB - Association for Computational Linguistics (ACL)
Y2 - 1 August 2021 through 6 August 2021
ER -