Computational analysis of adjuncts in ASD-STE100 for the NLP parser ARTEMIS

  1. Cortés-Rodríguez, Francisco José 1
  2. Rodríguez-Juárez, Carolina 2
  1. 1 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

  2. 2 Universidad de Las Palmas de Gran Canaria
    info

    Universidad de Las Palmas de Gran Canaria

    Las Palmas de Gran Canaria, España

    ROR https://ror.org/01teme464

Journal:
VIAL, Vigo international journal of applied linguistics

ISSN: 1697-0381

Year of publication: 2023

Issue: 20

Pages: 107-147

Type: Article

DOI: 10.35869/VIAL.V0I20.4356 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: VIAL, Vigo international journal of applied linguistics

Abstract

Texts written in Simplified Technical English present semantic and syntactic restrictions with respect to standard English that should be considered in the implementation of natural language processing systems dealing with controlled natural languages. This paper explores the syntax and semantics of adjuncts in a controlled natural language, namely, the Simplified Technical English (ASD-STE100) used in the Airbus corpus with a view to observing how the peculiarities identified in the behaviour of Airbus adverbials should be reflected in the computational treatment of these constituents. Thus, our main aim is to contribute to the computational implementation of the prototype ARTEMIS by designing the parsing rules and the catalogue of feature-bearing matrixes that encode the grammatical constraints of Airbus adjuncts. The parsing rules reflect the positional preferences of the various peripheral types and capture the semantic variability of adjuncts in the corpus. In addition, they provide a weight factor that predicts the scale of markedness of these constituents with respect to the different positions that they occupy in the clause. On the whole, these properties offer a precise description of the syntactic features of adverbials that will facilitate their automatic processing.

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