Paper: Exploring Various Knowledge In Relation Extraction

ACL ID P05-1053
Title Exploring Various Knowledge In Relation Extraction
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005

Extracting semantic relationships between en- tities is challenging. This paper investigates the incorporation of diverse lexical, syntactic and semantic knowledge in feature-based rela- tion extraction using SVM. Our study illus- trates that the base phrase chunking information is very effective for relation ex- traction and contributes to most of the per- formance improvement from syntactic aspect while additional information from full parsing gives limited further enhancement. This sug- gests that most of useful information in full parse trees for relation extraction is shallow and can be captured by chunking. We also demonstrate how semantic information such as WordNet and Name List, can be used in fea- ture-based relation extraction to further im- prove the performance. Evaluation on ...