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

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

Criterios ontológicos en FunGramKB

[EN] Ontology engineering should be grounded on a protocol of well-founded guidelines concerning the structuring of the ontology as well as the elements to be included and their ontological properties. A sound methodology for ontology development involves a dramatic reduction of many common errors and inconsistencies in conceptual modelling, facilitating thus interoperatibility and knowledge sharing—particularly useful when a multipurpose resource is designed. In the natural language processing context, this paper describes the ontological commitments to which the FunGramKB Ontology is subject.[ES] Cualquier trabajo en ingeniería ontológica debe estar fundamentado en un protocolo de directrices bien definidas que no sólo organicen la estructuración de la ontología sino que además ayuden a determinar sus unidades ontológicas y propiedades. Una sólida metodología para el desarrollo de ontologías exige la eliminación de muchos de los errores e inconsistencias que se suelen cometer en el modelado ontológico, facilitando así la interoperatibilidad y el conocimiento compartido—especialmente útil cuando se diseña un recurso multipropósito. En el contexto del procesamiento del lenguaje natural, este artículo describe los compromisos ontológicos que la Ontología de FunGramKB debe cumplir.Financial support for this research has been provided by the DGI, Spanish Ministry of Education and Science, grant FFI2008-05035- C02-01/FILO. The research has been cofinanced through FEDER funds.Periñán Pascual, JC.; Arcas Túnez, F. (2010). Ontological commitments in FunGramKB. Procesamiento del Lenguaje Natural. (44):27-34. http://hdl.handle.net/10251/52170S27344

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

FunGramKB y el conocimiento cultural

[ES] Una base de conocimiento provista de información sobre entidades nombradas, i.e. entidades con nombre propio, resulta de suma importancia para algunas tareas del procesamiento del lenguaje natural, p.ej. la resolución de la anáfora. Por esta razón, en los últimos años han proliferado los proyectos orientados a la extracción automática de ese tipo de entidades, además de recuperar información semántica sobre ellas. En este sentido, dentro del marco de FunGramKB, nosotros pretendemos importar por medio de plantillas de proyección los datos almacenados en repositorios sobre el conocimiento cultural, el cual está configurado principalmente por entidades nombradas. Así, el objetivo de este artículo es describir el proceso semiautomático de migración del conocimiento cultural de DBpedia a los constructos cognitivos del Onomasticón de FunGramKB.Este trabajo forma parte de dos proyectos de investigación financiados por el Ministerio de Ciencia y Tecnología, códigos FFI2008-05035-C02-01 y FFI2010-15983.Periñán Pascual, JC.; Carrión Varela, MDLL. (2011). FunGramKB y el conocimiento cultural. Anglogermánica Online. (8):87-105. http://hdl.handle.net/10251/30980S87105

Introducción a FunGramKB

Los vínculos entre el procesamiento del lenguaje natural y la lingüística teórica no han sido ni tan numerosos ni tan productivos como podríamos esperar. En los últimos veinte años, ha aumentado progresivamente la tendencia a utilizar enfoques estadísticos, los cuales resultan más económicos y rápidos de implementar. No obstante, con el fin de realizar algún avance en el procesamiento semántico y pragmático, se requiere un nuevo paradigma en los sistemas de comprensión del lenguaje, en el cual se conjuguen los resultados investigadores de disciplinas como la ciencia cognitiva, la lingüística y la inteligencia artificial. Con este objetivo, se diseñó e implementó computacionalmente la base de conocimiento FunGramKB. Este artículo presenta brevemente los diversos módulos que configuran los niveles léxico, gramatical y conceptual en esta base de conocimiento, destaca aquellas investigaciones que han influido de manera más determinante en nuestro modelo teórico y además describe el papel de este recurso en un sistema del procesamiento del lenguaje natural

The process of constructing ontological meaning based on criminal law verbs

This study intends to account for the process involved in the construction of the conceptual meaning of verbs (#EVENTS) directly related to legal aspects of terrorism and organized crime based on the evidence provided by the Globalcrimeterm Corpus and the consistent application of specific criteria for term extraction. The selected 49 concepts have eventually been integrated in the Core Ontology of FunGramKB (Functional Grammar Knowledge Base), a knowledge base which is founded on the principles of deep semantics and is also aimed at the computational development of the Lexical Constructional Model (www.fungramkb.com). To achieve this purpose, key phases of the COHERENT methodology (Periñán Pascual & Mairal Usón 2011) are followed, particularly those which involve the modelling, subsumption and hierarchisation of the aforementioned verbal concepts. The final outcome of this research shows that most of the apparently specialised conceptual units should eventually be included in the Core Ontology instead of the specific Globalcrimeterm Subontology, due to the fact that the semantic content of their corresponding lexical units can be found in widely used learner`s dictionaries and, consequently, this conceptual information is not only shared by the experts in the field but also by the layperson and the average speaker of the language

The situated common-sense knowledge in FunGramKB

It has been widely demonstrated that expectation-based schemata, along the lines of Lakoff's propositional Idealized Cognitive Models, play a crucial role in text comprehension. Discourse inferences are grounded on the shared generalized knowledge which is activated from the situational model underlying the text surface dimension. From a cognitive-plausible and linguistic-aware approach to knowledge representation, FunGramKB stands out for being a dynamic repository of lexical, constructional and conceptual knowledge which contributes to simulate human-level reasoning. The objective of this paper is to present a script model as a carrier of the situated common-sense knowledge required to help knowledge engineers construct more "intelligent" natural language processing systems.Periñán Pascual, JC. (2012). The situated common-sense knowledge in FunGramKB. Review of Cognitive Linguistics. 10(1):184-214. doi:10.1075/rcl.10.1.06perS18421410

Crimes against children: an apparently terminological knowledge representation of entities in FunGramKB

[EN] This article describes an example of the difficulties involved in the construction of a term-based satellite (or domain-specific) ontology integrated in FunGramKB –a lexico-conceptual knowledge base for the computational processing of natural language (Periñán-Pascual & Arcas-Túnez 2004, 2007, 2010a; Periñán-Pascual & Mairal-Usón 2009, 2010). The main hypothesis is that the multilevel model of FunGramKB Core Ontology can be connected to terminological satellite ontologies in order to minimize redundancy and maximize information (Periñán-Pascual & Arcas-Túnez 2010b). To this end we follow the four-phase COHERENT methodology (Periñán-Pascual & Mairal-Usón 2011): COnceptualization, HiErarchization, REmodelling and refinemeNT. In doing so, the paper furnishes substantial evidence on the structuring of a set of concepts borrowed from criminal law, an apparently terminological domain (cf. Breuker, Valente & Winkels 2005; Valente 2005; Breuker, Casanovas & Klein 2008). The Globalcrimeterm corpus has been used as an empirical foundation (Felices-Lago & Ureña-Gómez Moreno 2012, 2014). To illustrate this process, we have selected the superordinate basic concept +CRIME_00 (Alameda-Hernández & Felices-Lago 2016) and its basic and terminal subordinate concepts in the domains of organized crime and terrorism (all of them under the metaconcept #ENTITY), particularly those crimes referring predominantly to children or involving children with other vulnerable groups. The creation of specific definitions for the target concepts in this paper uses COREL (a conceptual representation language (Periñán-Pascual & Mairal-Usón 2010)) and the following upper-level conceptual path: #ENTITY> #PHYSICAL> #PROCESS> +OCCURRENCE_00> +CRIME_00. Consequently, the modelling, subsumption and hierarchisation of concepts such as $ABDUCTION_00,$CHILD_ABUSE_00, $CHILD_PORNOGRAPHY_00,$COERCE_D_00, $CHILD_TRAFFICKING_00,$MOLEST_D_00, $FORCED_LABOUR, among others, are presented.This article is based on research carried out within the framework of the Project FFI2014-53788-C3-1-P, which is funded by the Spanish Ministry of Economy and Competitiveness, and entitled: Development of a virtual laboratory for natural language processing from a functional paradigm. It is also based on the previous Project code no. FFI2010-15983: Development of a subontology in a multilingual context (English, Spanish and Italian): Using FunGramKB in the field of international cooperation in criminal matters: Terrorism and organised crime”.Alameda Hernández, Á.; Felices Lago, Á. (2017). Crimes against children: an apparently terminological knowledge representation of entities in FunGramKB. Journal of Computer-Assisted Linguistic Research. 1(1):1-19. https://doi.org/10.4995/jclr.2017.7785SWORD1191