Pattern Learning for Relation Extraction with a Hierarchical Topic Model

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We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant supervision using relations from the knowledge base FreeBase, but do not require any manual heuristic nor manual seed list selections. Results show that the learned patterns can be used to extract new relations with good precision.

Enrique Alfonseca, Katja Filippova, Jean-Yves Delo

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ACL 2012 | Computational Linguistics | Freebase | Heuristic | Lexical Patterns |

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Added	29 Sep 2012
Updated	29 Sep 2012
Type	Journal
Year	2012
Where	ACL
Authors	Enrique Alfonseca, Katja Filippova, Jean-Yves Delort, Guillermo Garrido

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Pattern Learning for Relation Extraction with a Hierarchical Topic Model

ACL 2012 | Computational Linguistics | Freebase | Heuristic | Lexical Patterns |

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