We present DEFIE, an approach to large-scale Information Extraction (IE) based on a syntactic-semantic analysis of textual definitions. Given a large corpus of definitions we leverage syntactic dependencies to reduce data sparsity, then disambiguate the arguments and content words of the relation strings, and finally exploit the resulting information to organize the acquired relations hierarchically. The output of DEFIE is a high-quality knowledge base consisting of several million automatically acquired semantic relations.

Large-Scale information extraction from textual definitions through deep syntactic and semantic analysis / DELLI BOVI, Claudio; Telesca, Luca; Navigli, Roberto. - In: TRANSACTIONS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS. - ISSN 2307-387X. - ELETTRONICO. - 3:(2015), pp. 529-543.

Large-Scale information extraction from textual definitions through deep syntactic and semantic analysis

DELLI BOVI, CLAUDIO;NAVIGLI, ROBERTO
2015

Abstract

We present DEFIE, an approach to large-scale Information Extraction (IE) based on a syntactic-semantic analysis of textual definitions. Given a large corpus of definitions we leverage syntactic dependencies to reduce data sparsity, then disambiguate the arguments and content words of the relation strings, and finally exploit the resulting information to organize the acquired relations hierarchically. The output of DEFIE is a high-quality knowledge base consisting of several million automatically acquired semantic relations.
2015
Open Information Extraction; Information Extraction; syntactic-semantic analysis
01 Pubblicazione su rivista::01a Articolo in rivista
Large-Scale information extraction from textual definitions through deep syntactic and semantic analysis / DELLI BOVI, Claudio; Telesca, Luca; Navigli, Roberto. - In: TRANSACTIONS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS. - ISSN 2307-387X. - ELETTRONICO. - 3:(2015), pp. 529-543.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/845278
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