Constructing large proposition databases

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

With the advent of massive online encyclopedic corpora such as Wikipedia, it has become possible to apply a systematic analysis to a wide range of documents covering a significant part of human knowledge. Using semantic parsers, it has become possible to extract such knowledge in the form of propositions (predicate―argument structures) and build large proposition databases from these documents. This paper describes the creation of multilingual proposition databases using generic semantic dependency parsing. Using Wikipedia, we extracted, processed, clustered, and evaluated a large number of propositions. We built an architecture to provide a complete pipeline dealing with the input of text, extraction of knowledge, storage, and presentation of the resulting propositions

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Computer Science

Keywords

  • Knowledge Discovery/Representation, Information Extraction, Information Retrieval, Semantics
Original languageEnglish
Title of host publicationProceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)
PublisherEuropean Language Resources Association (ELRA)
Pages3836-3839
ISBN (Electronic) 978-2-9517408-7-7
Publication statusPublished - 2012
Publication categoryResearch
Peer-reviewedYes
EventThe eighth international conference on Language Resources and Evaluation (LREC 2012) - Istanbul, Turkey
Duration: 2012 May 212012 May 27

Conference

ConferenceThe eighth international conference on Language Resources and Evaluation (LREC 2012)
CountryTurkey
CityIstanbul
Period2012/05/212012/05/27

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