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DWS at the 2016 Open Knowledge Extraction Challenge: A Hearst-Like Pattern-Based Approach to Hypernym Extraction and Class Induction

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Semantic Web Challenges (SemWebEval 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 641))

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Abstract

In this paper we present a system for the 2016 edition of the Open Knowledge Extraction (OKE) Challenge. The OKE challenge promotes research in automatic extraction of structured content from textual data and its representation and publication as Linked Data. The proposed system addresses the second task of the challenge, namely “Class Induction and entity typing for Vocabulary and Knowledge Base enrichment” and combines state-of-the-art lexically-based Natural Language Processing (NLP) techniques with lexical and semantic knowledge bases to first extract hypernyms from definitional sentences and second select the most suitable class of the extracted hypernyms from those available in the DOLCE foundational ontology.

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Notes

  1. 1.

    http://webdatacommons.org/isadb/.

  2. 2.

    The largest publicly available crawl of the Web.

  3. 3.

    In this case \(f=1\) and \(Context=s\).

  4. 4.

    In this case \(f=|matching sentences|\) and Context is the result of concatenation of a random sample of at most five matching sentences.

  5. 5.

    A standard set of english stop words is used to select only content words.

  6. 6.

    Corresponding to sentence http://www.ontologydesignpatterns.org/data/oke-challenge/task-2/sentence-117#char=0,381.

  7. 7.

    Corresponding to definiendum http://www.ontologydesignpatterns.org/data/oke-challenge/task-2/sentence-117#char=2,17.

  8. 8.

    http://aksw.org/Projects/GERBIL.html.

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Acknowledgement

This work was partially funded by the Junior-professor funding programme of the Ministry of Science, Research and the Arts of the state of Baden-Württemberg, Germany (project “Deep semantic models for high-end NLP applications”).

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Authors and Affiliations

  1. Research Group Data and Web Science, University of Mannheim, Mannheim, Germany

    Stefano Faralli & Simone Paolo Ponzetto

Authors
  1. Stefano Faralli
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  2. Simone Paolo Ponzetto
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Correspondence to Stefano Faralli .

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Editors and Affiliations

  1. IT Systems Engineering, Hasso-Plattner Institute, Potsdam, Germany

    Harald Sack

  2. Leibniz Universität Hannover , Hannover, Germany

    Stefan Dietze

  3. Elsevier B.V. , Amsterdem, The Netherlands

    Anna Tordai

  4. Universität Bonn , Bonn, Germany

    Christoph Lange

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Faralli, S., Ponzetto, S.P. (2016). DWS at the 2016 Open Knowledge Extraction Challenge: A Hearst-Like Pattern-Based Approach to Hypernym Extraction and Class Induction. In: Sack, H., Dietze, S., Tordai, A., Lange, C. (eds) Semantic Web Challenges. SemWebEval 2016. Communications in Computer and Information Science, vol 641. Springer, Cham. https://doi.org/10.1007/978-3-319-46565-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-46565-4_4

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