Paper: Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations

ACL ID P11-1055
Title Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web’s natural language text. Knowledge-based weak supervision, using structured data to heuristically label a training corpus, works towards this goal by enabling the automated learning of a potentially unbounded number of relation extractors. Recently, researchers have developed multi- instance learning algorithms to combat the noisy training data that can come from heuristic labeling, but their models assume relations are disjoint — for example they cannot extract the pair Founded(Jobs, Apple) and CEO-of(Jobs, Apple). This paper presents a novel approach for multi-instance learning with overlapping re- lations that combines a sentence-level extrac- tion model with a simple, corpus-level ...