Pattern Learning for Relation Extraction with a Hierarchical Topic Model

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Pattern Learning for Relation Extraction with a Hierarchical Topic Model

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by Enrique Alfonseca , Jean-yves Delort , Guillermo Garrido

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BibTeX

@MISC{Alfonseca_patternlearning,
    author = {Enrique Alfonseca and Jean-yves Delort and Guillermo Garrido},
    title = {Pattern Learning for Relation Extraction with a Hierarchical Topic Model},
    year = {}
}

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Abstract

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. 1

Keyphrases

hierarchical topic model relation extraction pattern learning good precision manual seed list selection learned pattern state ontological relation new relation knowledge base freebase lexical pattern distant supervision

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