Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104953
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Title: Classifiers of Mandarin alphabetical words with character-alphabet structure
Authors: Zhao, X 
Hsu, YY 
Huang, CR 
Issue Date: 2024
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2024, v. 14514, p. 130-145
Abstract: Mandarin alphabetical words (MAWs) refer to the code-mixing of Romanized letters and characters such as X光 ‘X-ray’ in the Mandarin lexicon. Previous studies have mainly focused on MAWs’ formation but lacked empirical evidence regarding their morpho-syntactic behaviours. Classifiers have been used to infer nominals’ semantic properties and characteristics. An intriguing yet less explored issue is the classifier-selection pattern of MAWs and MAWs’ morpho-syntactic idiosyncrasies. We adopt a corpus-based approach to handle this issue. Assuming that a MAW’s classifier is motivated by the head of that MAW, we hypothesize that when a MAW is integrated into the Mandarin lexicon, its dominant classifiers will be the semantically more specific ones and not the neutral classifier. We show that MAWs share a dominant compounding structure in Mandarin and that MAW's classifier is decided by that head even when the head is represented by alphabets.
Keywords: Classifiers
Code-mixing
Corpus-based approach
Mandarin Alphabetical Words
Publisher: Springer
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-981-97-0583-2_11
Rights: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024
This version of the proceeding paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-981-97-0583-2_11.
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