Abstract:The Functional Grammar Knowledge Base (FunGramKB), (Periñán-Pascual and Arcas-Túnez 2010) is a multipurpose lexico-conceptual knowledge base designed to be used in different Natural Language Processing (NLP) tasks. It is complemented with the ARTEMIS (Automatically Representing Text Meaning via an Interlingua-based System) application, a parsing device linguistically grounded on Role and Reference Grammar (RRG) that transduces natural language fragments into their corresponding grammatical and semantic structures. This paper unveils the different phases involved in its parsing routine, paying special attention to the treatment of argumental constructions. As an illustrative case, we will follow all the steps necessary to effectively parse a For-Benefactive structure within ARTEMIS. This methodology will reveal the necessity to distinguish between Kernel constructs and L1-constructions, since the latter involve a modification of the lexical template of the verb. Our definition of L1-constructions leads to the reorganization of the catalogue of FunGramKB L1-constructions, formerly based on Levin's (1993) alternations. Accordingly, a rearrangement of the internal configuration of the L1-Constructicon within the Grammaticon is proposed.
This paper offers the basic guidelines of a formalized version of the Lexical Constructional Model (LCM; Ruiz de Mendoza & Mairal Usón, 2008, 2011; Ruiz de Mendoza & Galera, 2014), the Formalized Lexical-Constructional Grammar (FL_CxG), which will pave the way for future computational developments, such as parsers or lexical databases. The FL_CxG deploys (i) the typologically oriented syntactic apparatus of Role and Reference Grammar (Van Valin, 2005; Van Valin & LaPolla, 1997), (ii) the catalogue of constructional units arranged in a 4-layer typology, as proposed by the LCM, and (iii) some insights for semantic representations from the Generative Lexicon Theory (Pustejovsky, 1995; Pustejovsky & Batiukova, 2019), and Minimal English (Goddard, 2018). All the components of the FL_CxG (lexical units and construct(ion)s) are formally encoded as Typed Feature Structures in the format of Attribute Value Matrixes. These units are to be understood as constraints operating in the unification processes which underlie the generation/decoding of a given fragment of language.
RESUMENEste artículo persigue demostrar que las noticias de la prensa británica, indiferentemente a la clase de diario en que se publican, up-, mid-o down-market, presentan unas características genéricas comunes basadas en las relaciones semánticas que establecen sus elementos léxicos y en su organización textual que pueden ser probadas por medio de un análisis de la cohesión léxica como el diseñado por M. Hoey (1991). A la vista de los resultados estadísticos del análisis del corpus respecto a vínculos y conexiones léxicas, así como a su estructuración esquemática, se concluye que todos grupos de diario muestran las mismas características genéricas derivadas de su finalidad informativa, desmintiendo con ello disimilitudes debidas al formato o la clase social de los lectores. Palabras clave: género, cohesión, cohesión léxica, noticias de prensa ABSTRACTThis paper tries to show that news items, even if published in different types of journal (up-mid or down-market), can be generically characterized on the basis of their textual organization and of the semantic relations established by their lexical items. Contrary to the traditional view that presupposes divergences between broadsheets and tabloids, using M. Hoey's (1991) analysis of lexical cohesion as a tool we will prove statistically that news items present common characteristics derived from their basic generic purpose, namely, providing information.
ARTEMIS (Automatically Representing Text Meaning via an Interlingua-based System), is a natural language processing device, whose ultimate aim is to be able to understand natural language fragments and arrive at their syntactic and semantic representation. Linguistically, this parser is founded on two solid linguistic theories: the Lexical Constructional Model and Role and Reference Grammar. Although the rich semantic representations and the multilingual character of Role and Reference Grammar make it suitable for natural language understanding tasks, some changes to the model have proved necessary in order to adapt it to the functioning of the ARTEMIS parser. This paper will deal with one of the major modifications that Role and Reference Grammar had to undergo in this process of adaptation, namely, the substitution of the operator projection for feature-based structures, and how this will influence the description of function words in ARTEMIS, since they are strongly responsible for the encoding of the grammatical information which in Role and Reference Grammar is included in the operators. Currently, ARTEMIS is being implemented for the controlled natural language ASD-STE100, the Aerospace and Defence Industries Association of Europe Simplified Technical English, which is an international specification for the preparation of technical documentation in a controlled language. This controlled language is used in the belief that its simplified nature makes it a good corpus to carry out a preliminary testing of the adequacy of the parser. In this line, the aim of this work is to create a catalogue of function words in ARTEMIS for ASD-STE100, and to design the lexical rules necessary to parse the simple sentence and the referential phrase in this controlled language.
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