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Lista de candidatos sometidos a examen:
1) fungramkb (*)
(*) Términos presentes en el nuestro glosario de lingüística

1) Candidate: fungramkb


Is in goldstandard

1
paper corpusSignosTxtLongLines375 - : Resumen: Una de las tareas más tediosas en la labor diaria de los profesionales del derecho es la búsqueda de información en el ámbito jurídico. Con el fin de implementar aplicaciones avanzadas del procesamiento del lenguaje natural en este dominio, hemos desarrollado un modelo de representación del conocimiento especializado orientado a la semántica profunda dentro del marco de FunGramKB, una base de conocimiento léxico-conceptual multilingüe de propósito general . Más concretamente, el resultado de esta investigación ha dado como fruto una ontología terminológica sobre derecho penal en el dominio del terrorismo y el crimen organizado transnacional para ser utilizada en sistemas inteligentes que permitan la comprensión automática del discurso legal. El objetivo de este artículo es la descripción de la metodología empleada en el desarrollo de dicha ontología, centrándonos en la descripción de la herramienta que asiste al lingüista en el proceso de adquisición y conceptualización de lo

2
paper corpusSignosTxtLongLines375 - : FunGramKB^[27]3 (Periñán-Pascual & Arcas-Túnez, 2007b, 2010; Mairal-Usón & Periñán-Pascual, 2009; Periñán-Pascual & Mairal-Usón, 2010) es una base de conocimiento léxico-gramático-conceptual multipropósito diseñada principalmente para su uso en sistemas del PLN y, más concretamente, para aplicaciones que requieran la comprensión del lenguaje. Por una parte, esta base de conocimiento es ‘multipropósito’ en el sentido de que es tanto multifuncional como multilingüe. De esta manera, FunGramKB ha sido diseñada con el fin de ser potencialmente reutilizada en diversas tareas del PLN (por ejemplo: recuperación y extracción de información, traducción automática, sistemas basados en el diálogo, etc .) y con diversas lenguas (alemán, búlgaro, catalán, español, francés, inglés e italiano). Por otra parte, FunGramKB comprende tres niveles principales de conocimiento (i.e. léxico, gramatical y conceptual), cada uno de los cuales está constituido por diversos módulos independientes aunq

3
paper corpusSignosTxtLongLines375 - : Las Ontologías Satélites de FunGramKB se construyen como módulos conceptuales específicos de un dominio especializado, los cuales deben estar conectados a la Ontología Nuclear, ya que:

4
paper corpusSignosTxtLongLines375 - : Desde el punto de vista de la ingeniería del conocimiento, el desarrollo de cualquier Ontología Satélite en FunGramKB sigue una metodología de trabajo dividida en las siguientes fases:

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paper corpusSignosTxtLongLines375 - : ontológicas que se puedan establecer con dicho concepto. En definitiva, y en la línea de este último modelo, el umbral de productividad de un concepto básico c en FunGramKB vendrá definido por una métrica que tenga en consideración dos factores determinantes: el número de conceptos subordinados a c y el número de predicaciones en que aparece c en otros postulados de significado .

6
paper corpusSignosTxtLongLines453 - : Partiendo de un análisis lingüístico cualitativo basado en ejemplos de corpus, este artículo presenta un tratamiento computacional de varias construcciones, a saber, construcciones argumentales, construcciones implicativas y construcciones ilocutivas. De este modo, nuestro objetivo es ofrecer una representación formal de construcciones gramaticales de diferente naturaleza y complejidad. Para ello empleamos una base de conocimiento léxico-conceptual para sistemas de procesamiento del lenguaje natural denominada FunGramKB, cuyo gramaticón es una implementación computacional de la arquitectura del modelo construccionista basado en el uso llamado Modelo Léxico Construccional .

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paper corpusSignosTxtLongLines453 - : Jackendoff, 2004, inter alios), since, in this model, grammatical constructions of varied formal and functional complexity are parsimoniously assigned different places and functions within the same architecture. Such a holistic design is suitable for a computational environment that seeks to include both the propositional and the non-propositional dimensions of meaning. Thus, the LCM distributes heterogeneous constructions across four levels of meaning representation, each of which is computationally implemented in the Grammaticon of FunGramKB: level 1 deals with argument-structure constructions (e .g. He looked for a metal pipe and hammered it flat on one end (GBAC, 2013)), level 2 address implicational constructions (e.g. Don’t you honey me!; GBAC, 2007), level 3 focuses on illocutionary constructions (e.g. Can you open the door?; GBAC, 2001), and level 4 is concerned with discourse structure (e.g. Just because I forgive you doesn’t mean I forget; GBAC, 2014). In this paper we shall

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paper corpusSignosTxtLongLines453 - : Luzondo, A. & Jiménez, R. (2014). FrameNet and FunGramKB: A comparison of two computational resources for semantic knowledge representation . In B. Nolan & C. Periñán (Eds.), Language processing and grammars: The role of functionally oriented computational models (pp. 197-232). Amsterdam: John Benjamins. [ [136]Links ]

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paper corpusSignosTxtLongLines453 - : ^2 ^[165]Periñán and Mairal (2011) explain the methodology behind the creation of the Ontology of FunGramKB. For reasons of space, we shall only provide a brief explanation of this core component. The Ontology of FunGramKB is divided into three separate, albeit interrelated, subontologies in which the metaconcepts #ENTITIES, #EVENTS, and #QUALITIES respectively arrange in cognitive dimensions the following parts of speech: (i ) nouns, (ii) verbs, and (iii) adjectives. This type of organization stems from the fact that subsumption or IS-A is the only taxonomic relation permitted in the knowledge base.This contrasts with the approach adopted in FrameNet, for example, in which several frame-to-frame relations are posited (see ^[166]Ruppenhofer et al., 2010). These, however, have been shown to be problematic for NLP as far as reasoning is concerned (see ^[167]Ovchinnikova, Vieu, Oltramari, Borgo & Alexandrov, 2010). Conceptual, lexical and grammatical information is available through the NLP

10
paper corpusSignosTxtLongLines500 - : FunGramKB is grounded on two robust and complementary linguistic models: (i ) the projectionist model of Role and Reference Grammar (RRG)^[39]^2 (^[40]Van Valin & LaPolla, 1997; Van Valin, 2005), which provides the knowledge base with some basic assumptions related to the linking algorithm for the merging of lexical structures into constructional configurations (for example, Aktionsart ascription, macrorole assignment, status of variables, or logical structures, to name but a few); and (ii) the Lexical Constructional Model (LCM) (^[41]Mairal & Ruiz de Mendoza-Ibáñez, 2008; ^[42]Ruiz de Mendoza-Ibáñez & Mairal, 2008; ^[43]Ruiz de Mendoza-Ibáñez, 2013; ^[44]Ruiz de Mendoza-Ibáñez & Galera, 2014), which contributes to providing a layered structure of meaning construction that has helped to “fully integrate constructional meaning into RRG to deepen semantic processing” (^[45]Periñán-Pascual, 2013: 206). The LCM also offers a notion of construction that is more adequate for the computational

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paper corpusSignosTxtLongLines500 - : The knowledge base FunGramKB is lexico-conceptual because it distinguishes three knowledge levels of analysis which consist of independent, but interrelated modules, as represented in [50]Figure 1:

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paper corpusSignosTxtLongLines500 - : Here we show the CLS that is automatically generated for the predicate ‘spread’, and which includes FunGramKB ontologial concepts, an Aktionsart operator and a constructional operator (CONSTR-L1) that encodes constructional meaning:

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paper corpusSignosTxtLongLines500 - : In the last step in the parsing process, the CLS has to be automatically transduced into “a purely semantic conceptual representation in COREL” (^[61]Fumero & Díaz, 2017: 37). COREL (Conceptual Representation Language) is the machine-readable metalanguage that is used in the conceptual semantic representation of CLSs “that serves as the input for the reasoning engine” (^[62]Van Valin & Mairal 2014: 217), as shown below in the COREL scheme for the L1-locative construction that appears in the Grammaticon module in FunGramKB:

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paper corpusSignosTxtLongLines500 - : Of the different modules that constitute FunGramKB, it is the Lexicon and the Grammaticon that we will be focusing on in this research study. We will be specifically revising one of the attributes in the core grammar component in the Lexicon which has to do with the inventory of argumental constructions in which verbs can take part: L1- constructions.^[63]^5 The notion of construction, which is directly linked to the Grammaticon module (where constructional schemata are stored in different Constructicon modules), needs to be clearly and unequivocally defined in FunGramKB, as Periñán-Pascual himself highlights: “A key issue in this module [Grammaticon] is the definition of ‘construction’” (Periñán-Pascual, 2013: 213 ).

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paper corpusSignosTxtLongLines500 - : 3. Argumental constructions in FunGramKB: A computational perspective

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paper corpusSignosTxtLongLines500 - : The analysis of the alternating behaviour of the location argument has led us to propose the following inventory of L1-constructions in FunGramKB (as shown in [83]Table 2) that involve a change in the location argument taking into account the justifying criteria suggested so far:

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paper corpusSignosTxtLongLines500 - : The intransitive locative construction allows the locative argument (adjunct) to be the subject of the structure as a result of marked macrorole assignment following the Actor-Undergoer Macrorole Assignment Hierarchy (^[89]Van Valin, 2005). The fact that there is a case of marked macrorole assignment triggers the realization of the other non-selected potential macrorole argument (the original Theme) as a non-macrorole argument encoded as a ‘with’-phrase. In [90]Figure 3 below, you can see the CLS and the COREL scheme for this construction in FunGramKB:

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paper corpusSignosTxtLongLines500 - : The image impression construction might resemble ‘putting’ verbs in the locative construction since in both cases something is placed on a surface, but differs in the sense that with ‘creation’ verbs (e.g. ‘engrave’, ‘imprint’, ‘tattoo’, etc.), as a result of the event described by the verb, a new entity is created (i.e. a tattoo, an inscription, etc.). These verbs are ascribed to the Aktionsart active accomplishment, a type of event that is not changed by the construction. The kernel construct of these verbs in FunGramKB (exemplified in (11)) involves two arguments whose thematic roles, as explained in Section 1, are defined according to their metaconceptual distribution: a Theme, which in the metaconcept #CREATION is defined as the entity that creates another (‘members’ in example (11 )) and a Referent, conceived as the entity that is created by another entity (‘their initials’ in (11)). It is also common to find a prepositional phrase that should be analysed as an adjunct (an op

Evaluando al candidato fungramkb:


2) constructions: 7 (*)
3) conocimiento: 7 (*)
4) verbs: 6 (*)
5) constructional: 6 (*)
6) periñán-pascual: 6
8) conceptual: 5
9) grammaticon: 5 (*)
10) construcciones: 5 (*)
12) macrorole: 5 (*)
13) argument: 5 (*)
14) entity: 4 (*)
15) representation: 4 (*)
16) ontología: 4 (*)
18) mairal: 4
20) computational: 4 (*)

fungramkb
Lengua: eng
Frec: 94
Docs: 4
Nombre propio: 18 / 94 = 19%
Coocurrencias con glosario: 12
Puntaje: 12.962 = (12 + (1+6.28540221886225) / (1+6.56985560833095)));
Candidato aceptado

Referencias bibliográficas encontradas sobre cada término

(Que existan referencias dedicadas a un término es también indicio de terminologicidad.)
fungramkb
: Fumero, M. C. & Díaz, A. (2017). The interaction of parsing rules and argument-predicate constructions: Implications for the structure of the Grammaticon in FunGramKB. Revista de Lingüística y Lenguas Aplicadas, 12, 33-44.
: FunGramKB comprises three major knowledge levels that consist of several independent, yet related, modules:
: Mairal, R. & Periñán-Pascual, C. (2016). Representing constructional schemata in the FunGramKB Grammaticon. In J. Fleischhauer, A. Latrouite & R. Osswald (Eds.), Explorations of the syntax-semantics interface (pp. 77-108). Düsseldorf: Düsseldorf University Press.
: Periñán, C. & Mairal, R. (2011). The COHERENT methodology in FunGramKB. Onomázein, 24, 13-33.
: Periñán-Pascual, C. & Arcas-Túnez, F. (2005). Microconceptual-Knowledge Spreading in FunGramKB. Proceedings of the 9th IASTED International Conference on Artificial Intelligence and Soft Computing (pp. 239-244). Anaheim-Calgary-Zúrich: ACTA Press.
: Periñán-Pascual, C. & Arcas-Túnez, F. (2010). Ontological commitments in FunGramKB. Procesamiento del Lenguaje Natural, 44, 27-34.
: Periñán-Pascual, C. & Arcas-Túnez, F. (2014). The implementation of the FunGramKB CLS Constructor. In B. Nolan & C. Periñán-Pascual (Eds.), Language processing and grammars: The role of functionally oriented computational models (pp. 165-196). Amsterdam: John Benjamins .