Open Information Extraction from the Web

8 years 11 months ago
Open Information Extraction from the Web
Traditionally, Information Extraction (IE) has focused on satisfying precise, narrow, pre-specified requests from small homogeneous corpora (e.g., extract the location and time of seminars from a set of announcements). Shifting to a new domain requires the user to name the target relations and to manually create new extraction rules or hand-tag new training examples. This manual labor scales linearly with the number of target relations. This paper introduces Open IE (OIE), a new extraction paradigm where the system makes a single data-driven pass over its corpus and extracts a large set of relational tuples without requiring any human input. The paper also introduces TEXTRUNNER, a fully implemented, highly scalable OIE system where the tuples are assigned a probability and indexed to support efficient extraction and exploration via user queries. We report on experiments over a 9,000,000 Web page corpus that compare TEXTRUNNER with KNOWITALL, a state-of-the-art Web IE system. TEXTRUN...
Michele Banko, Michael J. Cafarella, Stephen Soder
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Authors Michele Banko, Michael J. Cafarella, Stephen Soderland, Matthew Broadhead, Oren Etzioni
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