Paper: Recognizing Relation Expression between Named Entities based on Inherent and Context-dependent Features of Relational words

ACL ID C10-2047
Title Recognizing Relation Expression between Named Entities based on Inherent and Context-dependent Features of Relational words
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

This paper proposes a supervised learn- ing method to recognize expressions that show a relation between two named en- tities, e.g., person, location, or organiza- tion. The method uses two novel fea- tures, 1) whether the candidate words in- herently express relations and 2) how the candidate words are influenced by the past relations of two entities. These features together with conventional syntactic and contextual features are organized as a tree structure and are fed into a boosting-based classification algorithm. Experimental re- sults show that the proposed method out- performs conventional methods.