Cognitive modules of an NLP knowledge base for language understanding

Algunas aplicaciones del procesamiento del lenguaje natural, p.ej. la traducción automática, requieren una base de conocimiento provista de representaciones conceptuales que puedan reflejar la estructura del sistema cognitivo del ser humano. En cambio, tareas como la indización automática o la extracción de información pueden ser realizadas con una semántica superficial. De todos modos, la construcción de una base de conocimiento robusta garantiza su reutilización en la mayoría de las tareas del procesamiento del lenguaje natural. El propósito de este artículo es describir los principales módulos cognitivos de FunGramKB, una base de conocimiento léxico-conceptual multipropósito para su implementación en sistemas del procesamiento del lenguaje natural.Some natural language processing systems, e.g. machine translation, require a knowledge base with conceptual representations reflecting the structure of human beings’ cognitive system. In some other systems, e.g. automatic indexing or information extraction, surface semantics could be sufficient, but the construction of a robust knowledge base guarantees its use in most natural language processing tasks, consolidating thus the concept of resource reuse. The objective of this paper is to describe FunGramKB, a multipurpose lexicoconceptual knowledge base for natural language processing systems. Particular attention will be paid to the two main cognitive modules, i.e. the ontology and the cognicon

Cognitive modules of an NLP knowledge base for language understanding

[EN] Some natural language processing systems, e.g. machine translation, require a knowledge base with conceptual representations reflecting the structure of human beings’ cognitive system. In some other systems, e.g. automatic indexing or information extraction, surface semantics could be sufficient, but the construction of a robust knowledge base guarantees its use in most natural language processing tasks, consolidating thus the concept of resource reuse. The objective of this paper is to describe FunGramKB, a multipurpose lexicoconceptual knowledge base for natural language processing systems. Particular attention will be paid to the two main cognitive modules, i.e. the ontology and the cognicon.[ES] Algunas aplicaciones del procesamiento del lenguaje natural, p.ej. la traducción automática, requieren una base de conocimiento provista de representaciones conceptuales que puedan reflejar la estructura del sistema cognitivo del ser humano. En cambio, tareas como la indización automática o la extracción de información pueden ser realizadas con una semántica superficial. De todos modos, la construcción de una base de conocimiento robusta garantiza su reutilización en la mayoría de las tareas del procesamiento del lenguaje natural. El propósito de este artículo es describir los principales módulos cognitivos de FunGramKB, una base de conocimiento léxico-conceptual multipropósito para su implementación en sistemas del procesamiento del lenguaje natural.Periñán Pascual, JC.; Arcas Túnez, F. (2007). Cognitive modules of an NLP knowledge base for language understanding. Procesamiento del Lenguaje Natural. (39):197-204. http://hdl.handle.net/10251/52122S1972043

SPECIAL ISSUE: New Insights into Meaning Construction and Knowledge Representation

The ten papers that have been selected for publication in this special issue entitled “New Insights into Meaning Construction and Knowledge Representation” present the outcomes of recent relevant investigations conducted both within Spain and international contexts, and which have been supported by research projects related to various aspects of meaning and knowledge representation. In particular, the findings presented in this volume combine insights from theoretical and computational linguistics in the context of natural language understanding, with parallel studies conducted within the realm of cognitive linguistics with special reference to the role of metaphor and other cognitive operations in meaning construction. Many of the contributions that are presented here are examples of the integration and collaboration between linguistics and other diverse fields such as Natural Language Processing (NLP), semantic memory loss disorders, aeronautic engineering or computer science, that reveal the need to link contemporary linguistics to other arenas that may have a direct and significant impact on society..

The process of building the upper-level hierarchy for the aircraft structure ontology to be integrated in FunGramKB

In this article we collect a corpus of texts which operate with a controlled language (ASD Simplified Technical English) in order to facilitate the development of a new domain-specific ontology (the aircraft structure) based on a technical discipline (aeronautical engineering) included in the so called “hard” sciences. This new repository should be compatible with the Core Ontology and the corresponding English Lexicon in FunGramKB (a multipurpose lexico-conceptual knowledge base for natural language processing (NLP)), and, in the same vein, should eventually give support to aircraft maintenance management systems. By contrast, in previous approaches we applied a stepwise methodology for the construction of a domain-specific subontology compatible with FunGramKB systems in criminal law, but the high occurrence of terminological banalisation and the scarce number of specific terms, due to the social nature of the discipline, were added problems to the most common NLP difficulties (polysemy and ambiguity). Taking into consideration previous results and the complexity of this task, here we only intend to take the first step towards the modelling of the aircraft ontology: the development of its taxonomic hierarchy. Consequently, the hierarchy starts with the whole system (i.e., an aircraft) and follows the traditional decomposition of the system down to the elementary components (top-down approach). At the same time, we have collected a corpus of 2,480 files of aircraft maintenance instructions, courtesy of Airbus in Seville. For the bottom-up approach (under construction), we consult specialised references end explore the corpus through the identification and extraction of term candidates with DEXTER, an online multilingual workbench especially designed for the discovery and extraction of terms

The configuration of a philosophical parameter in the subontology #ENTITY of FunGramKB: The case of axiology

The Functional Grammar Knowledge Base FunGramKB (FGKB), on the one hand, is a multipurpose lexico-conceptual knowledge base for natural language processing (NLP) systems. It comprises three major interrelated knowledge level modules: lexical, grammatical and conceptual. At the conceptual level the core ontology is presented as a hierarchical catalogue of the concepts that a person has in mind. Here is where semantic knowledge is stored in the form of meaning postulates. On the other hand, axiology is considered to be a primitive, basic or key parameter, among others, in the architecture of meaning construction at different levels.  This parameter can be traced back to the three subontologies in which FunGramKB can be split: #ENTITY for nouns, # EVENT for verbs, and #QUALITY for adjectives. In this paper we shall concentrate on the category # ENTITY and explore how the main categories and features of the axiological parameter (good-bad or positive-negative [+/-]) are represented and encoded within FunGramKB ontology, particularly inside semantic properties such as the meaning postulates

An account of selection restrictions in role and reference grammar

The goal of this paper is to explore how selection restrictions can be easily incorporated in the Ontology in the form of conceptual schemata like thematic frames (TFs) and meaning postulates (MPs). These, in turn, will be connected to the RRG logical structures via conceptual logical structures, which are abstract representational mechanisms that bridge the gap between the cognition-oriented TFs and MPs in the Ontology, and the particular lexicosyntactic idiosyncrasies represented in logical structures (Periñán and Mairal, “Bringing”). As for selection restrictions, or selectional preferences, they are stated in TFs and MPs when they exert constraints typically related to the cognitive situations displayed by the events. The domain of POSSESSION is employed to illustrate this kind of preferences within an ontologyEl objetivo de este trabajo es explorar cómo las restricciones de selección pueden ser fácilmente incorporadas a la ontología en forma de esquemas conceptuales como son los marcos temáticos (MMTT) y los postulados de significado (PPSS). Estos, a su vez, estarán conectados a las estructuras lógicas de la GPR a través de las estructuras lógicas conceptuales, que son unos mecanismos abstractos de representación que hacen de puente entre los MMTT y los PPSS de la ontología, y las idiosincrasias léxico-sintácticas recogidas en las estructuras lógicas (Periñán y Mairal, “Bringing”). En cuanto a las restricciones de selección o preferencias de selección, se expresan en los MMTT y en los PPSS cuando ejercen constreñimientos normalmente relacionados con las situaciones cognitivas mostradas por los eventos. Se muestra el dominio de la posesión para ilustrar este tipo de preferencias dentro de una ontologíaFinancial support for this research has been provided by the DGI, Spanish Ministry of Science and Innovation, grants no. HUM2007-65755, no. FFI2008-05035-C02-01 (co-financed through FEDER funds), and no. FFI2010-17610/FILO

A framework of analysis for the evaluation of automatic term extractors

[EN] Following previous research on automatic term extraction, the primary aim of this paper is to propose a more robust and consistent framework of analysis for the comparative evaluation of term extractors. Within the different views for software quality outlined in ISO standards, our proposal focuses on the criterion of external quality and in particular on the characteristics of functionality, usability and efficiency together with the subcharacteristics of suitability, precision, operability and time behavior. The evaluation phase is completed by comparing four online open-access automatic term extractors: TermoStat, GaleXtract, BioTex and DEXTER. This latter resource forms part of the virtual functional laboratory for natural language processing (FUNK Lab) developed by our research group. Furthermore, the results obtained from the comparative analysis are discussed.Financial support for this research has been provided by the Spanish Ministry of Economy, Competitiveness and Science, grant FFI2014-53788-C3-1-P.Periñán-Pascual, C.; Mairal-Usón, R. (2018). A framework of analysis for the evaluation of automatic term extractors. VIAL. Vigo International Journal of Applied Linguistics. 15:105-125. https://doi.org/10.35869/vial.v0i15.88S1051251

Multilingualism and conceptual modelling

[EN] One of the leading motivations behind the multilingual semantic web is to make resources accessible digitally in an online global multilingual context. Consequently, it is fundamental for knowledge bases to find a way to manage multilingualism and thus be equipped with those procedures for its conceptual modelling. In this context, the goal of this paper is to discuss how common-sense knowledge and cultural knowledge are modelled in a multilingual framework. More particularly, multilingualism and conceptual modelling are dealt with from the perspective of FunGramKB, a lexico-conceptual knowledge base for natural language understanding. This project argues for a clear division between the lexical and the conceptual dimensions of knowledge. Moreover, the conceptual layer is organized into three modules, which result from a strong commitment towards capturing semantic knowledge (Ontology), procedural knowledge (Cognicon) and episodic knowledge (Onomasticon). Cultural mismatches are discussed and formally represented at the three conceptual levels of FunGramKB.We would like to thank Guadalupe Aguado-de-Cea, Christopher Butler, Lachlan Mackenzie, Elena Montiel-Ponsoda and Brian Nolan for detailed comments on the first draft of this paper. Any error is ours. Financial support for this research has been provided by the Spanish Ministry of Education and Science, grants FFI2011-29798-C02-01 and FFI2014-53788-C3-1-P.Mairal-Usón, R.; Periñán-Pascual, C. (2016). Multilingualism and conceptual modelling. Circulo de Linguistica Aplicada a la Comunicacion. 66:244-277. https://doi.org/10.5209/CLAC.52774S2442776

Enhancing a role and reference grammar approach to English motion constructions in a Natural Language Processing environment

This paper puts forward a finer-grained computational treatment of the English caused-motion construction (e.g. He kicked the ball into the net) within a knowledge base for natural language processing systems called FunGramKB. This computational project is largely based on Role and Reference Grammar (RRG), which is a functional projectionist theory of language. We argue that the RRG-based characterization of the caused-motion construction in FunGramKB is insufficient to account for the semantic and syntactic complexity of realizations such as He walked the dog to the park, I will show you out, or Mac flew Continental to Bush International Airport. Thus, drawing on insights from Constructions Grammars, three minimally distinct transitive motion sub-constructions are formalized within FunGramKB. It is through the inclusion of additional constructional schemas that the machine will be able to capture the various ways in which verbs and constructions interact to yield different input textsEste artículo presenta un tratamiento computacional más fino de la construcción de movimiento causado en inglés (por ejemplo, He kicked the ball into the net, “metió de una patada la pelota en la red”) en una base de conocimientos para sistemas de Procesamiento de Lenguaje Natural llamada FunGramKB. Este proyecto computacional se basa en gran medida en la Gramática del Papel y la Referencia (RRG), que es una teoría funcionalista del lenguaje. Argumentamos que la caracterización basada en la RRG de la construcción de movimiento causado en FunGramKB es insuficiente para explicar la complejidad semántica y sintáctica de realizaciones tales como He walked the dog to the park, I will show you out, or Mac flew Continental to Bush International Airport , “Sacó a pasear al perro al parque, Te enseño la salida, Mac voló Continental al Aeropuerto Internacional Bush”. Así, basándose en las propuestas de las Gramáticas de Construcciones, se formalizan dentro de FunGramKB tres sub-construcciones de movimiento transitivas ligeramente distintas. A través de la de esquemas constructivos adicionales la máquina será capaz de dar cuenta de las diversas formas en que interactúan los verbos y las construcciones para producir diferentes textos de entradaThe research projects on which this paper is based have received financial support from the Spanish Ministry of Economy and Competitiveness, grants no. FFI2013- 43593-P and FFI2014-53788-C3-1-