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Update: February 24, 2023 The new version of Termout.org is now online, so this web site is now obsolete and will soon be dismantled.

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

1) Candidate: computational


Is in goldstandard

1
paper corpusSignosTxtLongLines176 - : Landauer, T. (2002). On the computational basis of learning and cognition: Arguments from LSA [en línea] . Disponible en: [58]http://lsa.colorado.edu/papers/Ross-final-submit.pdf [ [59]Links ]

2
paper corpusSignosTxtLongLines176 - : Quesada, J., Kintsch, W. & Gómez, E. (2001). A computational theory of complex problem solving using the vector space model (part I): Latent semantic analysis, through the path of thousands of ants [en línea] . Disponible en: [79]http://lsa.colorado.edu/~quesadaj/pdf/THEORETICALfinal.PDF [ [80]Links ]

3
paper corpusSignosTxtLongLines417 - : Nonetheless, the two perspectives developed above do not have to oppose each other. McEnery and Wilson (2001) do not consider intuition and the corpus-based approach mutually exclusive but complementary. Zhang (2013) does not question this idea but he highlights that semantic prosody is less accessible only through intuition, and computation would contribute to a better and more complete approach towards semantic prosody: “it is computational research and corpus linguistics that make it possible to highlight its existence” (Zhang, 2013: 64 ).

4
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

5
paper corpusSignosTxtLongLines455 - : Human language is based on the use of discrete units (i.e., words) that interact in non-random ways to construct a large variety of sentences (^[26]Ferrer i Cancho & Solé, 2001). Typically, in any language, there are many words that can have more than one meaning, generating ambiguity that can only be resolved by analyzing the context of where the word occurs. In Computational Linguistics, Word Sense Disambiguation (WSD) is one of the most important and challenging current problems. WSD refers to the “ability to computationally determine which sense of a word is adequate depending on its use in a particular context” (^[27]Navigli, 2009: 3 ). WSD is considered to be the most important problem to solve in automated text understanding. It is, therefore, a crucial resource for applications such as machine translation (^[28]Vickrey, Biewald, Teyssier & Koller, 2005; ^[29]Carpuat & Wu, 2007; ^[30]Chan, Ng & Chiang, 2007), information retrieval (^[31]Zhong & Ng, 2012), information extraction

6
paper corpusSignosTxtLongLines455 - : Agirre, E., Bengoetxea, K., Gojenola, K. & Nivre, J. (2011). Improving dependency parsing with semantic classes. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short papers -Volume 2 (pp . 699-703). Association for Computational Linguistics. [ [143]Links ]

7
paper corpusSignosTxtLongLines500 - : On the computational representation of constructions: The place of locative constructions in a knowledge base

8
paper corpusSignosTxtLongLines500 - : ^1Steels (2017) revises the research programmes that have attempted to provide computational implementations that account for the way constructions are used in the parsing and production of utterances: Embodied Construction Grammar (Bergen & Chang, 2005 ), Fluid Construction Grammar (Steels, 2011), Sign-based Construction Grammar (Boas & Sag, 2012) and Template Construction Grammar (Barres & Lee, 2014).

9
paper corpusSignosTxtLongLines505 - : Partee, B. H. (2008). Symmetry and symmetrical predicates. En A. E. Kibrik, V. I. Belikov & B. V. Dobrovolsky (Eds.), Computational linguistics and intellectual technologies: Papers from the international conference “Dialogue” (pp . 606-611). Moscow: Institut Problem Informatiki. [ [144]Links ]

10
paper corpusSignosTxtLongLines510 - : A partir de una concepción eminentemente generativa y, por tanto, computacional del lenguaje natural, la Teoría del Lexicón Generativo, desarrollada por ^[64]Pustejovsky en diversos trabajos (1991, ^[65]1995, ^[66]1998, ^[67]2013), reacciona contra el estatismo de las teorías semánticas al uso a mediados del siglo xx, en tanto que aboga por la naturaleza dinámica del lenguaje; en este sentido: “The difficulty here for semantics and computational lexicons is that word sense enumeration cannot characterize all the possible meanings of the lexical item in the lexicon” (^[68]Pustejovsky, 1998: 46 ; ^[69]Piera, 2009; ^[70]Pustejovsky, Bouillon, Isahara, Kanzaki & Lee, 2013).

11
paper corpusSignosTxtLongLines595 - : Martin, J. R. (1996). Types of structure: Deconstructing notions of constituency in clause and text. En E. H. Hovy & D. R. Scott (Eds.), Computational and Conversational Discourse: Burning Issues - an Interdisciplinary Account (pp . 39-66). Heidelberg: Springer, NATO Advanced Science Institute Series F - Computer and Systems Sciences. [ [230]Links ]

Evaluando al candidato computational:


1) constructions: 8 (*)
2) grammar: 4 (*)
3) semantic: 4 (*)
4) gbac: 4
8) linguistics: 4 (*)
11) pustejovsky: 3

computational
Lengua: eng
Frec: 239
Docs: 67
Nombre propio: 3 / 239 = 1%
Coocurrencias con glosario: 4
Puntaje: 4.652 = (4 + (1+4.8073549220576) / (1+7.90689059560852)));
Candidato aceptado

Referencias bibliográficas encontradas sobre cada término

(Que existan referencias dedicadas a un término es también indicio de terminologicidad.)
computational
: According to the degree of coherence established by lexical repetition among the different levels of a computational hypertext, Puebla and Puchmüller (2006) classify links from a corpus made up of hyper-biographies into:
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