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Transitional probability predicts native and non‐native use of formulaic sequences
Author(s) -
Appel Randy,
Trofimovich Pavel
Publication year - 2017
Publication title -
international journal of applied linguistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.712
H-Index - 39
eISSN - 1473-4192
pISSN - 0802-6106
DOI - 10.1111/ijal.12100
Subject(s) - salient , identification (biology) , metric (unit) , word (group theory) , natural language processing , computer science , task (project management) , sequence (biology) , linguistics , artificial intelligence , yield (engineering) , psychology , cognitive psychology , engineering , operations management , botany , genetics , materials science , systems engineering , metallurgy , biology , philosophy
Formulaic sequences ( FSs ), or prefabricated multi‐word structures (e.g. on the other hand), are often difficult to identify objectively, and current corpus‐driven methods yield structurally incomplete, overlapping, or overly extended structures of questionable psychological validity and pedagogical usefulness. To address these limitations, this study evaluated transitional probability as a potential metric to improve the identification of FSs by presenting 100 four‐word sequences from the B ritish N ational C orpus, varying in transitional probabilities between words, to native and non‐native speakers of E nglish ( N = 293) in a sequence completion task (e.g. for the sake__). Results revealed that the application of transitional probability reduces many of the problems associated with current approaches to FS identification and can produce lists of FSs that are more functionally salient and psychologically valid.