Parsing wh-interrogative sentences within ARTEMIS

María Auxiliadora Martín Díaz

Autores/as

María Auxiliadora Martín Díaz Universidad de La Laguna

Resumen

Abstract. The linguistic foundation of Functional Grammar Knowledge Base (FunGramKB) is inspired on robust linguistic theories like Role and Reference Grammar (RRG, Van Valin, 2005) and the Lexical Constructional Model (LCM) (Mairal-Usón & Ruiz de Mendoza Ibáñez, 2008). Accordingly, its lexical and grammatical levels will allow the system to capture syntactic-semantic generalizations which can provide explanations and predictions of language phenomena (Periñán-Pascual & Arcas-Túnez, 2010: 2671). ARTEMIS (Automatically Representing Text Meaning via an Interlingua-Based System) comes into play as a prototype which exploits FunGramKB to pursue the simulation of natural language understanding. To guarantee a correct parsing, this application relies on a set of production rules where pertinent morphosyntactic information must be expediently encoded via AVMs, feature-bearing structures which can effectively constrain this process (Periñán-Pascual, 2013a: 223). Departing from Martín-Díaz (2017)’s account of Y/N-interrogatives, this paper aims at proposing the rules and AVMs necessary for the correct parsing of WH-interrogatives within ARTEMIS.

Keywords: WH-Questions; Role and Reference Grammar; ARTEMIS

Resumen. El fundamento lingüístico de Functional Grammar Knowledge Base (FunGramKB) se inspira en teorías lingüísticas como la Gramática del Papel y la Referencia (RRG) (Van Valin, 2005) y el Modelo Léxico-Construccional (LCM) (Mairal-Usón y Ruiz de Mendoza Ibáñez, 2008). Sus niveles léxico y gramatical permiten al sistema capturar generalizaciones sintáctico-semánticas con las que explicar y predecir fenómenos lingüísticos (Periñán-Pascual y Arcas-Túnez, 2010: 2671). El objetivo de ARTEMIS (Automatically Representing Text Meaning via an Interlingua-Based System) es la simulación de la comprensión del lenguaje natural y para ello utiliza FunGramKB. Este prototipo garantiza el correcto parseado con unas reglas de producción donde la información morfosintáctica pertinente debe codificarse mediante Matrices Atributo Valor (MAVs) que puedan restringir dicho proceso (Periñán-Pascual, 2013a: 223). Partiendo del análisis de Martín-Díaz (2017) para las interrogativas polares, este trabajo propone las reglas y MAVs necesarias para un parseado efectivo de las interrogativas inglesas con formas WH- en ARTEMIS.

Palabras clave: Preguntas con formas WH- inicial; Gramática del Papel y la Referencia; ARTEMIS

Biografía del autor/a

María Auxiliadora Martín Díaz, Universidad de La Laguna

María Auxiliadora Martín-Díaz is an Associate Professor in the Department of English and German Philology at the University of La Laguna where, among other things, she has lectured on a Master’s course on language technologies and text management. She is currently involved in a research project from UNED, entitled «Desarrollo de un laboratorio virtual para el procesamiento computacional de la lengua desde un paradigma funcional» (FF2014-53788-C3-1-P).

Citas

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