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© 2022 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Languages differ in how systematically and obligatorily they encode conceptual categories such as tense and aspect. By drawing on large parallel corpora, these differences can be exploited heuristically: expressive obligatoriness and the systematicity of a conceptual category in one language can function as a probe for other languages that do not (evidently) encode it. This study applies this method—called heuristic translation mining (HTM)—to viewpoint aspect in Mandarin (an aspect-oriented language) and Dutch (a non-aspect-oriented language). Specifically, it takes the Mandarin aspect markers 起来-qilai (“ingressive”) and 下去-xiaqu (“continuative”) and collects translation strategies for these markers from a corpus of five Mandarin novels and their Dutch translations. The outcomes are methodological, descriptive and theoretical in nature. Methodologically, it is shown how conceptual templates consisting of temporal boundaries and phases facilitate annotating specific types of viewpoint aspect consistently. Descriptively, the exercise indicates at which linguistic levels viewpoint aspect may be encoded in a non-aspect-oriented language. Theoretically, conducting an HTM analysis with several aspect markers at once makes it possible to quantify (non-)marking of conceptual content; it turns out that the types of viewpoint under study correspond to varying marking frequencies, which may correlate with conceptual complexity.

Details

Title
The Discovery of Aspect: A Heuristic Parallel Corpus Study of Ingressive, Continuative and Resumptive Viewpoint Aspect
Author
Bogaards, Maarten  VIAFID ORCID Logo 
First page
158
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
2226471X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2716549592
Copyright
© 2022 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.