Identifying Relations for Open Information Extraction
Identifying Relations for Open Information Extraction
authors Anthony Fader, Stephen Soderland and Oren Etzioni
venue Conference on Empirical Methods in Natural Language Processing
year 2011
abstract Open Information Extraction (IE) is the task of extracting assertions from massive corpora without requiring a pre-specified vocabulary. This paper shows that the output of state-of- the-art Open IE systems is rife with uninformative and incoherent extractions. To over- come these problems, we introduce two simple syntactic and lexical constraints on bi- nary relations expressed by verbs. We implemented the constraints in the ReVerb Open IE system, which more than doubles the area under the precision-recall curve relative to previous extractors such as TextRunner and WOE-pos. More than 30% of ReVerb's extractions are at precision 0.8 or higher— compared to virtually none for earlier systems. The paper concludes with a detailed analysis of ReVerb's errors, suggesting directions for future work.

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