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Whole-Part Relations Rule-Based Automatic Identification: Issues from Fine-Grained Error Analysis

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Human-Inspired Computing and Its Applications (MICAI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8856))

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Abstract

In this paper, we focus on the most frequent errors that occurred during the implementation of a rule-based module for semantic relations extraction, which has been integrated in STRING, a hybrid statistical and rule-based Natural Language Processing chain for Portuguese. We focus on whole-part relations (meronymy), that is, a semantic relation between an entity that is perceived as a constituent part of another entity, or a member of a set. In this case, we target the type of meronymy involving human entities and body-part nouns. We describe with some detail the decisions that were made in order to overcome the errors produced by the system and the solutions adopted to improve its performance.

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Author information

Authors and Affiliations

  1. Centro de Investigación en Computación (CIC), Instituto Politécnico Nacional (IPN), México D.F., Mexico

    Ilia Markov

  2. Universidade do Algarve/FCHS and CECL, Faro, Portugal

    Nuno Mamede

  3. Spoken Language Lab, INESC-ID Lisboa/L2F, Lisboa, Portugal

    Nuno Mamede & Jorge Baptista

  4. Universidade de Lisboa/IST, Lisboa, Portugal

    Jorge Baptista

Authors
  1. Ilia Markov
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  2. Nuno Mamede
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  3. Jorge Baptista
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Editor information

Editors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, Av. Juan Dios Bátiz s/n, Col. Nueva Industrial Vallejo, 07738, Mexico City, Mexico

    Alexander Gelbukh

  2. Área Académica de Computación y Electrónica, Carretera Pachuca-Tulancingo, Universidad Autónoma del Estado de Hidalgo, Km. 4.5, Col. Carboneras, Mineral de la Reforma, 42180, Hidalgo, Mexico

    Félix Castro Espinoza

  3. Facultad de ciencias, Universidad Autónoma Nacional de México, Ciudad Universitaria, México DF, Mexico

    Sofía N. Galicia-Haro

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Markov, I., Mamede, N., Baptista, J. (2014). Whole-Part Relations Rule-Based Automatic Identification: Issues from Fine-Grained Error Analysis. In: Gelbukh, A., Espinoza, F.C., Galicia-Haro, S.N. (eds) Human-Inspired Computing and Its Applications. MICAI 2014. Lecture Notes in Computer Science(), vol 8856. Springer, Cham. https://doi.org/10.1007/978-3-319-13647-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-13647-9_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13646-2

  • Online ISBN: 978-3-319-13647-9

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