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2018 | OriginalPaper | Buchkapitel

Unsupervised Slot Filler Refinement via Entity Community Construction

verfasst von : Zengzhuang Xu, Rui Song, Bowei Zou, Yu Hong

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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Abstract

Given an entity (query), slot filling aims to find and extract the values (slot fillers) of its specific attributes (slot types) from a large-scale of document collections. Most existing work of slot filling models slot fillers separately and only considers direct relations between slot fillers and query, ignoring other slot fillers in context. In this paper we propose an unsupervised slot filler refinement approach via entity community construction to filter out the incorrect fillers collaboratively. The community-based framework mainly consists of (1) filler community generated by a point-wise mutual information-based hierarchical clustering, and (2) query community constructed by a co-occurrence graph model.

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Vorheriges Kapitel Babbling - The HIT-SCIR System for Emotional Conversation Generation

Nächstes Kapitel Relation Linking for Wikidata Using Bag of Distribution Representation

queryID: SF13_ENG_038, in KBP 2013 ESF data set.

http://lucene.apache.org.

per:{cause_of_death, date_of_birth, date_of_death, age, charges} and

org:{date_founded, date_dissolved, number_of_employees_members, website}.

http://gibbslda.sourceforge.net.

With slot type per:parents.

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Titel: Unsupervised Slot Filler Refinement via Entity Community Construction
verfasst von: Zengzhuang Xu
Rui Song
Bowei Zou
Yu Hong
Verlag: Springer International Publishing
Buch: Natural Language Processing and Chinese Computing
Print ISBN: 978-3-319-73617-4

Electronic ISBN: 978-3-319-73618-1

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-73618-1_54

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