DCFEE: A Document-level Chinese Financial Event Extraction System based on Automatically Labeled Training Data

著者: Hang Yang, Yubo Chen, Kang Liu, Yang Xiao, Jun Zhao - Annual Meeting of the Association for Computational Linguistics, ACL 2018 被引用: 175

We present an event extraction framework to detect event mentions and extract events from the document-level financial news. Up to now, methods based on supervised learning paradigm gain the highest performance in public datasets (such as ACE 2005 1 , KBP 2015 2 ). These methods heavily depend on the manually labeled training data. However, in particular areas, such as financial, medical and judicial domains, there is no enough labeled data due to the high cost of data labeling process. Moreover, most of the current methods focus on extracting events from one sentence, but an event is usually expressed by multiple sentences in one document.