Paper: A Semantic Feature for Relation Recognition Using a Web-based Corpus

ACL ID I08-1057
Title A Semantic Feature for Relation Recognition Using a Web-based Corpus
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

Selecting appropriate features to represent an entity pair plays a key role in the task of relation recognition. However, existing syntactic features or lexical features cannot capture the interaction between two enti- ties because of the dearth of annotated rela- tional corpus specialized for relation recog- nition. In this paper, we propose a seman- tic feature, called the latent topic feature, which is topic-based and represents an en- tity pair at the semantic level instead of the word level. Moreover, to address the prob- lem of insufficiently annotated corpora, we propose an algorithm for compiling a train- ing corpus from the Web. Experiment results demonstrate that latent topic features are as effective as syntactic or lexical features. Moreover, the Web-based corpus can resolve th...