tailieunhanh - Báo cáo khoa học: "The Tradeoffs Between Open and Traditional Relation Extraction"

Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tailored to massive and heterogeneous corpora such as the Web. An Open IE system extracts a diverse set of relational tuples from text without any relation-specific input. How is Open IE possible? We analyze a sample of English sentences to demonstrate that numerous relationships are expressed using a compact set of relation-independent lexico-syntactic patterns, which can be learned by an Open IE system. . | The Tradeoffs Between Open and Traditional Relation Extraction Michele Banko and Oren Etzioni Turing Center University of Washington Computer Science and Engineering Box 352350 Seattle WA 98195 USA banko etzioni@ Abstract 1 Introduction Traditional Information Extraction IE takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tailored to massive and heterogeneous corpora such as the Web. An Open IE system extracts a diverse set of relational tuples from text without any relation-specific input. How is Open IE possible We analyze a sample of English sentences to demonstrate that numerous relationships are expressed using a compact set of relation-independent lexico-syntactic patterns which can be learned by an Open IE system. What are the tradeoffs between Open IE and traditional IE We consider this question in the context of two tasks. First when the number of relations is massive and the relations themselves are not pre-specified we argue that Open IE is necessary. We then present a new model for Open IE called O-CRF and show that it achieves increased precision and nearly double the recall than the model employed by Textrunner the previous state-of-the-art Open IE system. Second when the number of target relations is small and their names are known in advance we show that O-CRF is able to match the precision of a traditional extraction system though at substantially lower recall. Finally we show how to combine the two types of systems into a hybrid that achieves higher precision than a traditional extractor with comparable recall. Relation Extraction RE is the task of recognizing the assertion of a particular relationship between two or more entities in text. Typically the target relation . seminar location is given to the RE system as input along with hand-crafted extraction patterns or patterns learned from hand-labeled training examples Brin 1998 Riloff and .

• Báo cáo khoa học
• The Tradeoffs Between Open
• Traditional Relation Extraction
• Michele Banko and Oren Etzioni
• báo cáo khoa học
• báo cáo ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
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