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...

Click Here to View the Paper In XML Format