We present a new approach to relation extraction that requires only a handful of training examples. Given a few pairs of named entities known to exhibit or not exhibit a particular relation, bags of sentences containing the pairs are extracted from the web. We extend an existing relation extraction method to handle this weaker form of supervision, and present experimental results demonstrating that our approach can reliably extract relations from web documents.
REF presented an approach to extract relations from the Web using minimal supervision.
Learning to Extract Relations from the Web using Minimal Supervision
45th Annual Meeting of the Association of Computational Linguistics
Computer Science