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Corpus-Based Semantic Filtering in Discovering Derivational Relations

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2012)

Abstract

Derivational relations are an important part of the lexical semantics system in many languages, especially those of rich inflection. They represent wide variety of semantic oppositions. Analysis of morphological word forms in terms of prefixes and suffixes provides limited information about their semantics. We propose a method of semantic classification of the potential derivational pairs. The method is based on supervised learning, but requires only a list of word pairs assigned to the derivational relations. The classification was based on a combination of features describing distribution of a derivative and derivational base in a large corpus together with their morphological and morpho-syntactic properties. The method does not use patterns based on close co-occurrence of a derivative and its base. Two classification schemes were evaluated: a multiclass and a cascade of binary classifiers, both expressed good performance in experiments on the selected nominal derivational relations.

Partially financed by the Polish Ministry of Education and Science, Project N N516 068637.

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Piasecki, M., Ramocki, R., Minda, P. (2012). Corpus-Based Semantic Filtering in Discovering Derivational Relations. In: Ramsay, A., Agre, G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2012. Lecture Notes in Computer Science(), vol 7557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33185-5_2

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  • DOI: https://doi.org/10.1007/978-3-642-33185-5_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33184-8

  • Online ISBN: 978-3-642-33185-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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