The correlation between nativelike selection and prototypicality: a multilingual onomasiological case study using semantic embedding
<|reference_start|>The correlation between nativelike selection and prototypicality: a multilingual onomasiological case study using semantic embedding: In native speakers' lexical choices, a concept can be more readily expressed by one expression over another grammatical one, a phenomenon known as nativelike selection (NLS). In previous research, arbitrary chunks such as collocations have been considered crucial for this phenomenon. However, this study examines the possibility of analyzing the semantic motivation and deducibility behind some NLSs by exploring the correlation between NLS and prototypicality, specifically the onomasiological hypothesis of Grondelaers and Geeraerts (2003, Towards a pragmatic model of cognitive onomasiology. In Hubert Cuyckens, Ren\'e Dirven & John R. Taylor (eds.), Cognitive approaches to lexical semantics, 67-92. Berlin: De Gruyter Mouton). They hypothesized that "[a] referent is more readily named by a lexical item if it is a salient member of the category denoted by that item". To provide a preliminary investigation of this important but rarely explored phenomenon, a series of innovative methods and procedures, including the use of semantic embedding and interlingual comparisons, is designed. Specifically, potential NLSs are efficiently discovered through an automatic exploratory analysis using topic modeling techniques, and then confirmed by manual inspection through frame semantics. Finally, to account for the NLS in question, cluster analysis and behavioral profile analysis are conducted to uncover a language-specific prototype for the Chinese verb shang 'harm', providing supporting evidence for the correlation between NLS and prototypicality.<|reference_end|>
@article{zhang2024the,
    title={The correlation between nativelike selection and prototypicality: a
  multilingual onomasiological case study using semantic embedding},
    author={Huasheng Zhang},
    journal={arXiv preprint arXiv:2405.13529},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.13529},
    primaryClass={cs.CL}
}