Identifying Relations for Open Information Extraction


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 uninfor-mative and incoherent extractions. To overcome these problems, we introduce two simple syntactic and lexical constraints on binary 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.

Extracted Key Phrases

Showing 1-10 of 414 extracted citations
Citations per Year

617 Citations

Semantic Scholar estimates that this publication has received between 534 and 717 citations based on the available data.

See our FAQ for additional information.