Several grammatical models have shown a growing interest for the development of the conditions necessary to satisfy the so-called criterion of computational adequacy. Within Role and Reference Grammar (RRG [

FunGramKB is a multipurpose lexico-conceptual knowledge base for natural language processing systems, and more particularly, for natural language understanding. The linguistic layer of this knowledge-engineering project is grounded in compatible aspects of two linguistic accounts, namely, Role and Reference Grammar (RRG) and the Lexical Constructional Model (LCM). RRG, although originally a lexicalist approach, has recently incorporated constructional configurations into its descriptive and explanatory apparatus. The LCM has sought to understand from its inception the factors that constrain lexical-constructional integration. Within this theoretical context, this paper discusses the format of lexical entries, highly inspired in RRG proposals, and of constructional schemata, which are organized according to the descriptive levels supplied by the LCM. Both lexical and constructional structure is represented by means of Attribute Value Matrices (AVMs). Thus, the lexical and grammatical levels of FunGramKB are the focus of our attention here. Additionally, the need for a conceptualist approach to meaning construction is highlighted throughout our discussion.

Recent research has been done synergistically between FunGramKB, a lexical-conceptual knowledge base, and the lexical constructional model, a linguistic meaning construction model. since concepts are claimed to play an important role in the design of the cognitive-linguistic interface, this paper discusses the methodology adopted in structuring the basic conceptual level in the FunGramKB core ontology. more particularly, we describe our four-phase coHeRenT methodology (i.e. conceptualization + Hierarchization + Remodelling + refinemenT), which guided the cognitive mapping of the defining vocabulary in longman Dictionary of contemporary english.

Within the framework of FUNK Lab -a virtual laboratory for natural language processing inspired on a functionally-oriented linguistic theory like Role and Reference Grammar-, a number of computational resources have been built dealing with different aspects of language and with an application in different scientific domains, i.e. terminology, lexicography, sentiment analysis, document classification, text analysis, data mining etc. One of these resources is ARTEMIS (Automatically Representing TExt Meaning via an Interlingua-Based System), which departs from the pioneering work of Periñán-Pascual (2013) and Periñán-Pascual & Arcas (2014). This computational tool is a proof of concept prototype which allows the automatic generation of a conceptual logical structure (CLS) (cf. Mairal-Usón, Periñán-Pascual and Pérez 2012; Van Valin and Mairal-Usón 2014), that is, a fully specified semantic representation of an input text on the basis of a reduced sample of sentences. The primary aim of this paper is to develop the syntactic rules that form part of the computational grammar for the representation of simple clauses in English. More specifically, this work focuses on the format of those syntactic rules that account for the upper levels of the RRG Layered Structure of the Clause (LSC), that is, the core (and the level-1 construction associated with it), the clause and the sentence (Van Valin 2005). In essence, this analysis, together with that in Cortés-Rodríguez and Mairal-Usón (2016), offers an almost complete description of the computational grammar behind the LSC for simple clauses.

Los sistemas informáticos de comprensión del lenguaje natural requieren una base de conocimiento provista de representaciones conceptuales que reflejen la estructura del sistema cognitivo de los seres humanos. Aunque la semántica superficial puede ser suficiente en algunas otras aplicaciones computacionales, la construcción de una base de conocimiento robusta garantiza su reutilización en la mayoría de las tareas de procesamiento del lenguaje natural. En este escenario, FunGramKB se presenta como una base de conocimiento multipropósito cuyo modelo ha sido diseñado de manera específica para tareas de comprensión del lenguaje natural. Precisamente, uno de los elementos que han contribuido en forma notable al éxito de esta base de conocimiento ha sido el poder expresivo de su sistema notacional. El propósito de este artículo es describir la gramática, junto con su fundamentación teórica, del lenguaje de representación conceptual utilizado en FunGramKB.