/LING
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Lista de candidatos sometidos a examen:
1) frequent (*)
(*) Términos presentes en el nuestro glosario de lingüística
1) Candidate: frequent
Is in goldstandard
1
paper corpusSignosTxtLongLines396 - : The building metaphor vehicle co-occurrences with the corpus key words reveal certain frequency variations ([32]Table 2), in comparison to the original frequencies of the building vehicles listed in [33]Figure 1. On the whole, lower values were registered. Seven of the vehicles (‘elevator’, ‘floor’, ‘infrastructure’, ‘corner’, ‘building’, ‘roof’, ‘spiral’), which registered low frequencies in the corpus ([34]Figure 1), did not co-occur with the corpus key words. The most frequent vehicles in the corpus ([35]Figure 1: ‘build’, ‘foundation’, ‘construct’, ‘base’, and ‘architecture’ ) varied positions when they were examined for their co-occurrence with the key words. ‘Build’ remained the first most frequent vehicle, followed by ‘architecture’, ‘foundation’, ‘construct’, ‘block’, and ‘base’. Even though the results are relevant in that they provide evidence of the building metaphor theme in the corpus, the frequency variations detected in the
2
paper corpusSignosTxtLongLines396 - : ‘Window’, registering a co-occurrence of 54.5% with the key words, was used with a metaphorically originated terminological sense (Philip, 2010) for a software system element. Thus, its relevance for the building metaphorical theme is questionable. ‘Build’, the most frequent vehicle co-occurring with the corpus key words, registered a notably low percentage for this type of word combination: 30 .6%. ‘Build’ is a polysemous lexeme, used in highly conventionalized metaphorical expressions in a variety of contexts (see ‘build knowledge’ in example 5). The polysemous metaphoric uses of ‘build’ could explain why this is the most frequent building vehicle in project management discourse, despite its infrequent co-occurrence with the corpus key words (example 6).
3
paper corpusSignosTxtLongLines471 - : ^5 ^[152]Siyanova y Schmitt (2008) obtienen índices de correlación (Spearmann) entre la ordenación hecha por hablantes nativos de inglés y la basada en frecuencia de corpus que van del 0,58, para un conjunto de 31 colocaciones, al 0,74 para un conjunto de 10 colocaciones de frecuencia alta y se muestran relativamente optimistas en este sentido: “[…] N[ative] S[speaker]s not only have good intuitions of what collocations are very frequent and very infrequent in language but can also distinguish finer shades of frequency” (^[153]Siyanova & Schmitt, 2008: 445 ). ^[154]Siyanova y Spina (2015) emplean una metodología diferente. Según su análisis (esta vez tienen en cuenta la influencia de diversos factores en las respuestas de un grupo de hablantes), la frecuencia de cada una de las colocaciones del experimento no resulta un factor significativo en las estimaciones de sus informantes, pero sí la pertenencia de las colocaciones en cuestión a bandas de frecuencia alta, media, baja y muy baja. Las
4
paper corpusSignosTxtLongLines579 - : The following subfunctions include referring to other lectures (earlier and future), the course itself or other courses. The most frequent of them is ‘referring to earlier lectures’, present in almost half the lectures (49%):
5
paper corpusSignosTxtLongLines599 - : Another significant finding is the three most frequent verb boosters, which were found to be the same in the three corpora: ‘show’, ‘determine’ and ‘demonstrate’ . This pattern is in line with the previous finding of the high number of overlapping verb boosters in the three corpora. In addition, if a mean frequency of verb boosters is calculated for each corpus , the following values are given: 0.090 for Engineering, 0.061 for Medicine and 0.101 for Linguistics. This was used to identify the verb boosters with a significant normalised frequency, that is, a frequency above the mean value (highlighted in bold in [118]Table 4). There are five verbs like that in the Engineering corpus (‘show’, ‘determine’, ‘demonstrate’, ‘prove’ and ‘hold’) and four verbs in the Medicine and Linguistics corpora (‘show’, ‘determine’, ‘demonstrate’ and ‘establish’). As can be seen, a few different verbs appear on these two lists: ‘prove’ and ‘hold’ in Engineering and ‘establ
Evaluando al candidato frequent:
1) corpus: 10 (*)
3) build: 6
6) frecuencia: 4 (*)
7) verb: 4 (*)
8) colocaciones: 4 (*)
10) boosters: 4
12) vehicles: 3
13) determine: 3
14) show: 3
15) siyanova: 3
16) verbs: 3 (*)
17) lectures: 3
18) figure: 3 (*)
19) demonstrate: 3
20) co-occurrence: 3 (*)
frequent
Lengua: eng
Frec: 116
Docs: 46
Nombre propio: / 116 = 0%
Coocurrencias con glosario: 7
Puntaje: 7.878 = (7 + (1+5.90689059560852) / (1+6.8703647195834)));
Candidato aceptado
Referencias bibliográficas encontradas sobre cada término
(Que existan referencias dedicadas a un término es también indicio de terminologicidad.)| frequent |
: Ahonen-Myka, H. (2002). Discovery of frequent word sequences in text source. En Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery. London: U. K. |