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Deciphering the Nomenclature of Chemical Compounds in NooJ

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Formalizing Natural Languages: Applications to Natural Language Processing and Digital Humanities (NooJ 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1816))

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Abstract

This paper proposes a multifaceted approach to the design of an algorithm for the automatic recognition of chemical compounds in Croatian written as multiword expressions. The algorithm, which we have named the Croatian Chemical Compounds Module, consists of three layers: it uses (1) the NooJ dictionary as the basis for (2) a morphological grammar, and both (1) and (2) are used for (3) a syntactic grammar. This module supports not only single-unit words and homoatomic entities but also variations of chemical names recognized through a variety of suffixes, multiplicative prefixes, hyphens, Roman and Latin numerals, Greek letters, and round, square and curly brackets. Terminological diversity and inconsistency in writing style are discussed as they present a great problem for any such endeavor.

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Notes

  1. 1.

    Generally, suffixation is the most productive derivational process in Croatian. Babić [22] provides a list of 771 suffixes used for the derivation of all parts of speech (526 suffixes for nouns, 160 suffixes for adjectives, 61 suffixes for verbs and 24 suffixes for adverbs). On the other hand, there are only 77 prefixes used in the derivation of all major parts of speech.

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Author information

Authors and Affiliations

  1. Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia

    Kristina Kocijan

  2. Department of Linguistics, Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia

    Krešimir Šojat

  3. Ruđer Bošković Institute, Zagreb, Croatia

    Tomislav Portada

Authors
  1. Kristina Kocijan
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  2. Krešimir Šojat
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  3. Tomislav Portada
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Corresponding author

Correspondence to Kristina Kocijan .

Editor information

Editors and Affiliations

  1. University of Zadar, Zadar, Croatia

    Anita Bartulović

  2. University of Zadar, Zadar, Croatia

    Linda Mijić

  3. Université de Franche-Comté, Besançon, France

    Max Silberztein

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Kocijan, K., Šojat, K., Portada, T. (2024). Deciphering the Nomenclature of Chemical Compounds in NooJ. In: Bartulović, A., Mijić, L., Silberztein, M. (eds) Formalizing Natural Languages: Applications to Natural Language Processing and Digital Humanities. NooJ 2023. Communications in Computer and Information Science, vol 1816. Springer, Cham. https://doi.org/10.1007/978-3-031-56646-2_2

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  • DOI: https://doi.org/10.1007/978-3-031-56646-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56645-5

  • Online ISBN: 978-3-031-56646-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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