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Automatic Extraction of Verbal Phrasemes in the Electrical Energy Field with NooJ

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Formalizing Natural Languages: Applications to Natural Language Processing and Digital Humanities (NooJ 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1758))

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Abstract

The abundant presence of prefabricated sequences attracts the attention of linguists. Phraseological units are often problematic for foreign learners both receptively and productively. In addition, they think that the number of phraseological units is greater in FOS (French for specific purposes) than in general French. In the field of electrical energy, the abundant presence of phrasemes [verb + nominal group or not + preposition + nominal group] pose many problems for non-native engineer-learners. The modeling is done based on the observation of our corpus and dictionaries in electricity. By using three grammars (rational grammar, algebraic grammar and contextual grammar.), NOOJ allows us to extract 1389 phrase sequences for teaching. Also, a disambiguation can be set up to reject useless phrasemes by using the + EXCLUDE operator. At the end, for the selection of phrases for teaching, three criteria (frequency, fixation and pragmatic criterion) seem relevant to us for the identification or classification of phrases from the professional field for foreign learners.

This article is supported by the Fundamental Research Funds for the Central Universities (JB2021059).

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Authors and Affiliations

  1. North China Electric Power University, Beijing, China

    Tong Yang

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  1. Tong Yang
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Correspondence to Tong Yang .

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Editors and Affiliations

  1. Universidad Nacional de Rosario, Rosario, Argentina

    Mariana González

  2. Universidad Nacional de Rosario, Rosario, Argentina

    Silvia Susana Reyes

  3. Universidad Nacional de Rosario, Rosario, Argentina

    Andrea Rodrigo

  4. Université de Franche-Comté, Besancon, France

    Max Silberztein

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Yang, T. (2022). Automatic Extraction of Verbal Phrasemes in the Electrical Energy Field with NooJ. In: González, M., Reyes, S.S., Rodrigo, A., Silberztein, M. (eds) Formalizing Natural Languages: Applications to Natural Language Processing and Digital Humanities. NooJ 2022. Communications in Computer and Information Science, vol 1758. Springer, Cham. https://doi.org/10.1007/978-3-031-23317-3_8

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  • DOI: https://doi.org/10.1007/978-3-031-23317-3_8

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-23317-3

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