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Using variationism and learner corpus research to investigate grammatical gender marking in additional-language Spanish
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In: ISSN: 0023-8333 ; EISSN: 1467-9922 ; Language Learning ; https://hal.archives-ouvertes.fr/hal-03063653 ; Language Learning, Wiley, 2019, 69 (4), pp.911-942. ⟨10.1111/lang.12363⟩ (2019)
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Measuring coselectional constraint in learner corpora: A graph-based approach ...
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Measuring coselectional constraint in learner corpora: A graph-based approach ...
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Tracking developmental patterns in learner corpora: Focus on longitudinal studies ...
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Meunier, Fanny. - : Selected papers on theoretical and applied linguistics, 2019
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Verschmelzungen von Präposition und Artikel im Deutschen und ihr Erwerb von DaF-Lernern ...
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Verschmelzungen von Präposition und Artikel im Deutschen und ihr Erwerb von DaF-Lernern
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SkELL corpora as a part of the language portal Sõnaveeb: problems and perspectives ...
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SkELL corpora as a part of the language portal Sõnaveeb: problems and perspectives ...
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53 |
Automatic syntactic analysis of learner English ...
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Huang, Yan. - : Apollo - University of Cambridge Repository, 2019
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The present perfect in learner Englishes: A corpus-based case study on L1 German intermediate and advanced speech and writing
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A relevância da Pragmática no ensino do inglês aeronáutico: um estudo baseado em corpora ; The relevance of Pragmatics in aviation English teaching: a study based on corpora
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Prado, Malila Carvalho de Almeida. - : Biblioteca Digital de Teses e Dissertações da USP, 2019. : Universidade de São Paulo, 2019. : Faculdade de Filosofia, Letras e Ciências Humanas, 2019
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To be or not to be .? Analysis of misuses with be in a learner corpus in an online environment ; ¿Ser o no ser.? Análisis de errores con to be en un corpus de estudiantes en un entorno online
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Portuguese Native Language Identification
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Abstract:
This study presents the first Native Language Identification (NLI) study for L2 Portuguese.We used a sub-set of the NLI-PT dataset, containing texts written by speakers of five different native languages: Chinese, English, German, Italian, and Spanish.We explore the linguistic annotations available in NLI-PT to extract a range of (morpho-)syntactic features and apply NLI classification methods to predict the native language of the authors. The best results were obtained using an ensemble combination of the features, achieving 54:1% accuracy. ; info:eu-repo/semantics/publishedVersion
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Keyword:
Learner corpus; Native language identification; Portuguese
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URL: http://hdl.handle.net/10451/36514
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