Paper: Omni-word Feature and Soft Constraint for Chinese Relation Extraction

ACL ID P14-1054
Title Omni-word Feature and Soft Constraint for Chinese Relation Extraction
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Chinese is an ancient hieroglyphic. It is inat- tentive to structure. Therefore, segmenting and parsing Chinese are more difficult and less accurate. In this paper, we propose an Omni- word feature and a soft constraint method for Chinese relation extraction. The Omni-word feature uses every potential word in a sentence as lexicon feature, reducing errors caused by word segmentation. In order to utilize the structure information of a relation instance, we discuss how soft constraint can be used to cap- ture the local dependency. Both Omni-word feature and soft constraint make a better use of sentence information and minimize the in- fluences caused by Chinese word segmenta- tion and parsing. We test these methods on the ACE 2005 RDC Chinese corpus. The re- sults show a significant improvem...