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Multiagent Approach to Coreference Resolution Based on the Multifactor Similarity in Ontology Population

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Abstract

The multiagent approach to coreference resolution in the process of extracting information from texts in natural languages for ontology population is described. Special class agents corresponding to ontology classes are defined. They analyze the available information in the corresponding ontology instances. The results of this analysis are used for values to instance attribute, for detecting duplicates and equivalents of instances, for fixing coreferential relations, and for determining the weights of information connections used to resolve ambiguities. Coreferences are resolved taking into account a multifactor similarity measure between extracted objects that combines the semantic, context, positional, and grammar similarity measures. The class agents work within the multiagent approach to text analysis aimed at ontology population.

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Authors and Affiliations

  1. Ershov Institute of Information Systems, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090, Russia

    N. O. Garanina, E. A. Sidorova & A. S. Seryi

Authors
  1. N. O. Garanina
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  2. E. A. Sidorova
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  3. A. S. Seryi
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Correspondence to N. O. Garanina.

Additional information

Original Russian Text © N.O. Garanina, E.A. Sidorova, A.S. Seryi, 2018, published in Programmirovanie, 2018, Vol. 44, No. 1.

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Garanina, N.O., Sidorova, E.A. & Seryi, A.S. Multiagent Approach to Coreference Resolution Based on the Multifactor Similarity in Ontology Population. Program Comput Soft 44, 23–34 (2018). https://doi.org/10.1134/S0361768818010036

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  • DOI: https://doi.org/10.1134/S0361768818010036

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