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Improving Open Information Extraction for Semantic Web Tasks

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Transactions on Computational Collective Intelligence XXI

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 9630))

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Abstract

Open Information Extraction (OIE) aims to automatically identify all the possible assertions within a sentence. Results of this task are usually a set of triples (subject, predicate, object). In this paper, we first present what OIE is and how it can be improved when we work in a given domain of knowledge. Using a corpus made up of sentences in building engineering construction, we obtain an improvement of more than 18 %. Next, we show how OIE can be used at a base of a high-level semantic web task. Here we have applied OIE on formalisation of natural language definitions. We test this formalisation task on a corpus of sentences defining concepts found in the pizza ontology. At this stage, 70.27 % of our 37 sentences-corpus are fully rewritten in OWL DL.

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Notes

  1. 1.

    http://www.cs.ox.ac.uk/isg/ontologies/UID/00793.owl.

  2. 2.

    An exhaustive list of labels for phrases is available in the Penn Treebank [6].

  3. 3.

    http://www.w3.org/TR/owl-ref/#Restriction.

  4. 4.

    With a large ontology, such comparison must take advantage of an index for the sake of scalability.

  5. 5.

    http://www.w3.org/TR/sparql11-query/#propertypath-arbitrary-length.

  6. 6.

    \(r_i\) is the subsumption or the set of elements of a more complex restriction (URI of the restriction property, OWL keywords for the type of the restriction, etc.) as explained in the introduction of Sect. 4.3.

  7. 7.

    Only for better understanding. The choice of or would not have changed anything.

  8. 8.

    http://www.alchemyapi.com/.

  9. 9.

    For example http://www.pizzaexpress.com/our-food/our-restaurant-menu/mains/, http://www.nutritionrank.com/, etc.

  10. 10.

    Concepts’ tokens are usually surrounded by adjectives, adverbs, prepositions, etc.

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Authors and Affiliations

  1. Université Paris-Est, Centre Scientifique et Technique du Bâtiment (CSTB), Champs-sur-marne, France

    Cheikh Kacfah Emani & Bruno Fiès

  2. Université Lyon 1, LIRIS, CNRS, UMR5205, 69622, Villeurbanne, France

    Cheikh Kacfah Emani, Catarina Ferreira Da Silva & Parisa Ghodous

Authors
  1. Cheikh Kacfah Emani
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  2. Catarina Ferreira Da Silva
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  3. Bruno Fiès
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  4. Parisa Ghodous
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Correspondence to Cheikh Kacfah Emani .

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Editors and Affiliations

  1. Wrocław University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Swinburne University of Technology, Hawthorn, VIC, Australia

    Ryszard Kowalczyk

  3. CISUC, Department of Informatics Engineering, Universidade de Coimbra, Coimbra, Portugal

    Paulo Rupino da Cunha

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Emani, C.K., Da Silva, C.F., Fiès, B., Ghodous, P. (2016). Improving Open Information Extraction for Semantic Web Tasks. In: Nguyen, N.T., Kowalczyk, R., Rupino da Cunha, P. (eds) Transactions on Computational Collective Intelligence XXI. Lecture Notes in Computer Science(), vol 9630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49521-6_6

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  • DOI: https://doi.org/10.1007/978-3-662-49521-6_6

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  • Print ISBN: 978-3-662-49520-9

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