Paper: Learning to Extract Relations from the Web using Minimal Supervision

ACL ID P07-1073
Title Learning to Extract Relations from the Web using Minimal Supervision
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

We present a new approach to relation ex- traction that requires only a handful of train- ing examples. Given a few pairs of named entities known to exhibit or not exhibit a particular relation, bags of sentences con- taining the pairs are extracted from the web. We extend an existing relation extraction method to handle this weaker form of su- pervision, and present experimental results demonstrating that our approach can reliably extract relations from web documents.