<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The article tackles the problems of linguistic annotation in the Chinese texts presented in the Ruzhcorp – Russian-Chinese Parallel Corpus of RNC, and the ways to solve them. Particular attention is paid to the processing of Russian loanwords. On the one hand, we present the theoretical comparison of the widespread standards of Chinese text processing. On the other hand, we describe our experiments in three fields: word segmentation, grapheme-to-phoneme conversion, and PoS-tagging, on the specific corpus data that contains many transliterations and loanwords. As a result, we propose the preprocessing pipeline of the Chinese texts, that will be implemented in Ruzhcorp.</p>
</abstract>

The article tackles the problems of linguistic annotation in the Chinese texts presented in the Ruzhcorp – Russian-Chinese Parallel Corpus of RNC, and the ways to solve them. Particular attention is paid to the processing of Russian loanwords. On the one hand, we present the theoretical comparison of the widespread standards of Chinese text processing. On the other hand, we describe our experiments in three fields: word segmentation, grapheme-to-phoneme conversion, and PoS-tagging, on the specific corpus data that contains many transliterations and loanwords. As a result, we propose the preprocessing pipeline of the Chinese texts, that will be implemented in Ruzhcorp.

Linguistic Annotation of Translated Chinese Texts: Coordinating Theory, Algorithms and Data

Journal of Linguistics/Jazykovedný casopis

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The article tackles the problems of linguistic annotation in the Chinese texts presented in the Ruzhcorp – Russian-Chinese Parallel Corpus of RNC, and the ways...

Linguistic Annotation of Translated Chinese Texts: Coordinating Theory, Algorithms and Data

Pubblicato online: 30 dic 2021

Pagine: 590 - 602

DOI: https://doi.org/10.2478/jazcas-2021-0054

Parole chiave
Mandarin, Russian, parallel corpus, Chinese word segmentation (CWS), grapheme-to-phoneme conversion (G2P), PoS-tagging, code-switching detection

© 2021 Kirill I. Semenov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Linguistic Annotation of Translated Chinese Texts: Coordinating Theory, Algorithms and Data

Pubblicato online: 30 dic 2021

Pagine: 590 - 602

DOI: https://doi.org/10.2478/jazcas-2021-0054

Parole chiaveMandarin, Russian, parallel corpus, Chinese word segmentation (CWS), grapheme-to-phoneme conversion (G2P), PoS-tagging, code-switching detection

© 2021 Kirill I. Semenov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
Mandarin, Russian, parallel corpus, Chinese word segmentation (CWS), grapheme-to-phoneme conversion (G2P), PoS-tagging, code-switching detection