Paper: Relation Extraction Using Support Vector Machine

ACL ID I05-1033
Title Relation Extraction Using Support Vector Machine
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2005

This paper presents a supervised approach for relation extraction. We apply Support Vector Machines to detect and classify the relations in Automatic Content Extraction (ACE) corpus. We use a set of features including lexical to- kens, syntactic structures, and semantic entity types for relation detection and classification problem. Besides these linguistic features, we successfully utilize the distance between two entities to improve the performance. In relation detec- tion, we filter out the negative relation candidates using entity distance thresh- old. In relation classification, we use the entity distance as a feature for Support Vector Classifier. The system is evaluated in terms of recall, precision, and F- measure, and errors of the system are analyzed with proposed solution....