Paper: Discovering Relations Among Named Entities From Large Corpora

ACL ID P04-1053
Title Discovering Relations Among Named Entities From Large Corpora
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004
Authors

Discovering the significant relations embedded in documents would be very useful not only for infor- mation retrieval but also for question answering and summarization. Prior methods for relation discov- ery, however, needed large annotated corpora which cost a great deal of time and effort. We propose an unsupervised method for relation discovery from large corpora. The key idea is clustering pairs of named entities according to the similarity of con- text words intervening between the named entities. Our experiments using one year of newspapers re- veals not only that the relations among named enti- ties could be detected with high recall and precision, but also that appropriate labels could be automati- cally provided for the relations.