Top-down and bottom-up: A combined approach to slot filling

Zheng Chen, Suzanne Tamang, Adam Lee, Xiang Li, Marissa Passantino, Heng Ji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Slot Filling task requires a system to automatically distill information from a large document collection and return answers for a query entity with specified attributes ('slots'), and use them to expand the Wikipedia infoboxes. We describe two bottom-up Information Extraction style pipelines and a top-down Question Answering style pipeline to address this task. We propose several novel approaches to enhance these pipelines, including statistical answer re-ranking and Markov Logic Networks based cross-slot reasoning. We demonstrate that our system achieves state-of-the-art performance, with 3.1% higher precision and 2.6% higher recall compared with the best system in the KBP2009 evaluation.

Original languageEnglish (US)
Title of host publicationInformation Retrieval Technology - 6th Asia Information Retrieval Societies Conference, AIRS 2010, Proceedings
Pages300-309
Number of pages10
DOIs
StatePublished - 2010
Externally publishedYes
Event6th Asia Information Retrieval Societies Conference, AIRS 2010 - Taipei, Taiwan, Province of China
Duration: Dec 1 2010Dec 3 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6458 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Asia Information Retrieval Societies Conference, AIRS 2010
Country/TerritoryTaiwan, Province of China
CityTaipei
Period12/1/1012/3/10

Keywords

  • Information Extraction
  • Question Answering
  • Slot Filling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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