Corpus-based Open-Domain Event Type Induction
Jiaming Shen, Yunyi Zhang, Heng Ji, Jiawei Han · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · 2021
Traditional event extraction methods require predefined event types and their corresponding annotations to learn event extractors.These prerequisites are often hard to be satisfied in real-world applications.This work presents a corpus-based open-domain event type induction method that automatically discovers a set of event types from a given corpus.As events of the same type could be expressed in multiple ways, we propose to represent each event type as a cluster of predicate sense, object head pairs.Specifically, our method (1) selects salient predicates and object heads, (2) disambiguates predicate senses using only a verb sense dictionary, and (3) obtains event types by jointly embedding and clustering predicate sense, object head pairs in a latent spherical space.Our experiments, on three datasets from different domains, show our method can discover salient and high-quality event types, according to both automatic and human evaluations 1 .