Open Domain Atomic Event Extraction via Double Propagation for Chinese Text

Abstract

Recent studies show structured atomic event information is beneficial to represent the discourse semantic. However, extracting useful structured representation of events from open domain is a challenging problem. On one hand, previous event extraction methods on special domain, cannot be directly used for open domain because of domain limitation and predefined event pattern. On the other hand, atomic event extraction is simply regarded as a preprocessing step in previous related work, and few studies focus on atomic event extraction in open domain. In this paper, we propose an unsupervised method for Chinese event extraction in open domain. Being directed against the ellipsis and flexible sentence structure in Chinese text, the proposed method exploits double propagation (DP) to combine event extraction and event pattern generation, which does not require seed events or seed event patterns and is able to eliminate noise from syntactic parsing. Experimental results on standard benchmark show that our proposed method outperforms state-of-the-art algorithm.