Enhancing Event Causality Identification with Rationale and Structure-Aware Causal Question Answering

arXiv:2403.11129v1 Announce Type: new
Abstract: Document-level Event Causality Identification (DECI) aims to identify causal relations between two events in documents. Recent research tends to use pre-trained language models to generate the event causal relations. Whereas, these methods are prone to the errors of sequential generation due to multiple events in a document. Moreover, the potential structures such as event coreference and related causal chain are neglected. In this paper, we propose a multi-task learning framework to enhance event causality identification …

abstract arxiv causal causality cs.cl deci document documents errors event events generate identification identify language language models multiple question question answering relations research type