Paper: ReNoun: Fact Extraction for Nominal Attributes

ACL ID D14-1038
Title ReNoun: Fact Extraction for Nominal Attributes
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Search engines are increasingly relying on large knowledge bases of facts to provide direct answers to users? queries. How- ever, the construction of these knowledge bases is largely manual and does not scale to the long and heavy tail of facts. Open information extraction tries to address this challenge, but typically assumes that facts are expressed with verb phrases, and there- fore has had difficulty extracting facts for noun-based relations. We describe ReNoun, an open information extraction system that complements pre- vious efforts by focusing on nominal at- tributes and on the long tail. ReNoun?s ap- proach is based on leveraging a large on- tology of noun attributes mined from a text corpus and from user queries. ReNoun creates a seed set of training data by us- ing specialized pa...