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Unsupervised Slot Filler Refinement via Entity Community Construction

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Natural Language Processing and Chinese Computing (NLPCC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10619))

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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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Notes

  1. 1.

    queryID: SF13_ENG_038, in KBP 2013 ESF data set.

  2. 2.

    http://lucene.apache.org.

  3. 3.

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

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

  4. 4.

    http://gibbslda.sourceforge.net.

  5. 5.

    With slot type per:parents.

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Acknowledgement

This research work is supported by National Natural Science Foundation of China (Grants No. 61672367, No. 61672368, No. 61703293), the Research Foundation of the Ministry of Education and China Mobile, MCM20150602 and the Science and Technology Plan of Jiangsu, SBK2015022101 and BK20151222. The authors would like to thank the anonymous reviewers for their insightful comments and suggestions.

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Authors and Affiliations

  1. Soochow University, Suzhou, Jiangsu, China

    Zengzhuang Xu, Rui Song, Bowei Zou & Yu Hong

Authors
  1. Zengzhuang Xu
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  2. Rui Song
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  3. Bowei Zou
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  4. Yu Hong
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Corresponding author

Correspondence to Bowei Zou .

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Editors and Affiliations

  1. Fudan University, Shanghai, China

    Xuanjing Huang

  2. Singapore Management University, Singapore, Singapore

    Jing Jiang

  3. Peking University, Beijing, China

    Dongyan Zhao

  4. Peking University, Beijing, China

    Yansong Feng

  5. Soochow University, Suzhou, China

    Yu Hong

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Xu, Z., Song, R., Zou, B., Hong, Y. (2018). Unsupervised Slot Filler Refinement via Entity Community Construction. In: Huang, X., Jiang, J., Zhao, D., Feng, Y., Hong, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2017. Lecture Notes in Computer Science(), vol 10619. Springer, Cham. https://doi.org/10.1007/978-3-319-73618-1_54

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  • DOI: https://doi.org/10.1007/978-3-319-73618-1_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73617-4

  • Online ISBN: 978-3-319-73618-1

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