Open Information Extraction: The Second Generation
Etzioni, Oren (University of Washington) | Fader, Anthony (University of Washington) | Christensen, Janara (University of Washington) | Soderland, Stephen (University of Washington) | Mausam, - (University of Washington)
How do we scale information extraction to the massive size and unprecedented heterogeneity of the Web corpus? Beginning in 2003, our KnowItAll project has sought to extract high-quality knowledge from the Web. In 2007, we introduced the Open Information Extraction (Open IE) paradigm which eschews handlabeled training examples, and avoids domain-specific verbs and nouns, to develop unlexicalized, domain-independent extractors that scale to the Web corpus. Open IE systems have extracted billions of assertions as the basis for both common-sense knowledge and novel question-answering systems. This paper describes the second generation of Open IE systems, which rely on a novel model of how relations and their arguments are expressed in English sentences to double precision/recall compared with previous systems such as TEXTRUNNER and WOE.
Jul-19-2011
- Country:
- Asia > Middle East
- Iraq (0.05)
- Palestine > Gaza Strip
- Gaza Governorate > Gaza (0.04)
- Europe > Austria
- North America > United States
- California (0.04)
- Illinois > Cook County
- Chicago (0.04)
- Michigan (0.04)
- New York (0.04)
- Washington > King County
- Seattle (0.04)
- South America > Brazil (0.14)
- Asia > Middle East
- Genre:
- Research Report (0.34)
- Industry:
- Government > Regional Government (0.93)
- Technology: