RECLASSIFYING CHINESE PHRASE STRUCTURES: FROM FORMAL CONFIGURATION TO SEMANTIC RELATIONS
pdf

Keywords

Chinese phrase structures
semantic relations
formal configuration
phrase classification
Chinese syntax

How to Cite

Jiaze, S. ., & Mulyadi. (2026). RECLASSIFYING CHINESE PHRASE STRUCTURES: FROM FORMAL CONFIGURATION TO SEMANTIC RELATIONS (A. Lubis , Trans.). Lire Journal (Journal of Linguistics and Literature), 10(2), 97-113. https://doi.org/10.33019/lire.v10i2.604
Views
  • Abstract 0
  • pdf 0
Statistics reflect real-time downloads and views.

Abstract

The classification of Chinese phrase structures has traditionally been based on formal configuration, especially categories such as subject-predicate, verb-object, and modifier-head constructions. Although this approach is descriptively useful, it does not always explain why phrases with similar forms show different syntactic behavior, or why different forms may perform similar grammatical functions. This study therefore proposes a reclassification of Chinese phrase structures from formal configuration to semantic relations. Using a qualitative corpus-based descriptive design, the study analyzes 800 modern Chinese phrase tokens drawn from dictionaries, literary texts, news discourse, and linguistic studies. The findings show that semantic classification more effectively explains phenomena such as same form, different function, different form, same function, and form-meaning divergence. The study identifies core semantic relations, including agent-action, patient-action, instrument-action, location-action, object-action, restrictive, coordinative, and complementive relations, and demonstrates that these are closely related to sentence-convertibility, collocational compatibility, nominalization tendency, and ambiguity resolution. Through examples such as ???? (réncái ji?oliú), ???? (xuézh? t?olùn), ??? (shài tàiyáng), and ??? (xi? fángzi), the study argues that semantic relations provide a more adequate explanatory basis for Chinese phrase classification. It concludes that formal structure remains an important descriptive layer, while semantic relations offer a more explanatory framework for analysing Chinese phrase structures, especially in cases involving ambiguity, form–meaning divergence, and differences in syntactic behaviour. 

pdf

References

Bloomfield. (1980). 语言论 [Language] (Yuan Jiahua et al., Trans.). 商务印书馆.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Chen, L., Xu, S., Zhu, L., Zhang, J., Lei, X., & Yang, G. (2020). A deep learning based method for extracting semantic information from patent documents. Scientometrics, 125(1), 289–312. https://doi.org/10.1007/s11192-020-03634-y

Cheng, L. L.-S., & Sybesma, R. (2014). The syntactic structure of noun phrases. In The handbook of Chinese linguistics (pp. 248–274). Wiley. https://doi.org/10.1002/9781118584552.ch10

Chu, D., Wan, B., Li, H., Dong, S., Fu, J., Liu, Y., … Liu, H. (2022). A machine learning approach to spatio-temporal linguistic pattern analysis. International Journal of Geographical Information Science, 36(11), 2169–2193. https://doi.org/10.1080/13658816.2022.2087224

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage.

Ding, S., et al. (1961). 现代汉语语法讲话 [Lectures on modern Chinese grammar]. 商务印书馆.

Fan, X. (1980a). 关于结构和短语问题 [On structure and phrase issues]. 中国语文 [Chinese Language], (3).

Fan, X. (1980b). 说句子成分 [On sentence components]. 上海师范学院学报 [Journal of Shanghai Normal University], (1).

Gao, L., Li, H., Liu, Z., Liu, Z., Wan, L., & Feng, W. (2021). RNN-transducer based Chinese sign language recognition. Neurocomputing, 434, 45–54. https://doi.org/10.1016/j.neucom.2020.12.006

Hao, W. (2024). Extraction of complex sentence relationships based on formalized Chinese clause structures. In 2024 7th International Conference on Machine Learning and Natural Language Processing (MLNLP) (pp. 1–8). IEEE. https://doi.org/10.1109/MLNLP63328.2024.10800396

Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687

Huang, B., & Liao, X. (2011). 现代汉语(增订六版) [Modern Chinese] (6th rev. ed.). 高等教育出版社.

Li, Q., Li, L., Wang, W., Li, Q., & Zhong, J. (2020). A comprehensive exploration of semantic relation extraction via pre-trained CNNs. Knowledge-Based Systems, 194, 105488. https://doi.org/10.1016/j.knosys.2020.105488

Liu, D. (2004). 先秦汉语语序特点的类型学观照 [Typological view on pre-Qin Chinese word order]. 语言研究 [Language Studies], (1), 37–46.

Liu, Y., et al. (2024). How semantics works in Chinese relative clause processing: Insights from eye tracking. Frontiers in Psychology, 15, Article 1294132. https://doi.org/10.3389/fpsyg.2024.1294132

Lu, J. (2003). 现代汉语语法教程 [Tutorial on modern Chinese grammar]. 北京大学出版社.

Lü, S. (1979). 汉语语法分析问题 [Issues in Chinese grammar analysis]. 商务印书馆.

Lyu, S., & Li, Z. (2020). A comparative analysis of Chinese and English animal idioms. Theory and Practice in Language Studies, 10(6), 708–712. https://doi.org/10.17507/tpls.1006.12

Ma, J. (1983). 马氏文通 [Ma’s grammar]. 商务印书馆.

Mao, X., Huang, S., Li, R., & Shen, L. (2020). Automatic keywords extraction based on semantic features. IEEE Access, 8, 117528–117538. https://doi.org/10.1109/ACCESS.2020.3004628

Peng, W., Wei, Z., Song, J., Yu, S., & Sui, Z. (2021). Formalized Chinese sentence pattern structure and its hierarchical analysis. In Workshop on Chinese Lexical Semantics (pp. 286–298). Springer. https://doi.org/10.1007/978-3-031-06703-7_22

Qin, Y., Yang, W., Wang, K., Huang, R., Tian, F., Ao, S., & Chen, Y. (2021). Entity relation extraction based on semantic enhancement. Symmetry, 13(4), 539. https://doi.org/10.3390/sym13040539

Wan, Q., Wan, C., Xiao, K., Hu, R., Liu, D., & Liu, X. (2023). CFERE: Multi-type Chinese financial event relation extraction. Information Sciences, 630, 119–134. https://doi.org/10.1016/j.ins.2023.01.143

Wang, Y., Wang, L., Yang, Y., & Lian, T. (2021). SemSeq4FD: Integrating global semantic relationship for fault diagnosis text modeling. Expert Systems with Applications, 166, 114090. https://doi.org/10.1016/j.eswa.2020.114090

Wolpert, M., Ao, J., Zhang, H., Baum, S., & Steinhauer, K. (2024). The child the apple eats: Processing of argument structure in Mandarin verb-final sentences. Scientific Reports, 14, Article 20459. https://doi.org/10.1038/s41598-024-70318-5

Xu, J. (2014). 现代汉语篇章语言学 [Modern Chinese discourse linguistics]. 商务印书馆.

Xu, N., Chang, H., Xiao, B., Zhang, B., Li, J., & Gu, T. (2022). Relation extraction based on semantic dependency features. Buildings, 12(10), 1633. https://doi.org/10.3390/buildings12101633

Yang, H., & Li, Y. (1987). 《诗经》“名·是·动”式新考 [New study on “name-is-action” in Shijing]. 武汉大学学报(社会科学版) [Wuhan University Journal (Social Sciences)], (4), 80–86.

Yang, Y., & Baayen, R. H. (2025). Comparing the semantic structures of lexicon of Mandarin and English. Language and Cognition, 17, e10. https://doi.org/10.1017/langcog.2024.47

Yu, B., Deng, C., & Bu, L. (2022). Policy text classification algorithm based on BERT. In 2022 11th International Conference on Information Technology in Medicine and Education (ITME) (pp. 488–491). IEEE. https://doi.org/10.1109/ICTech55460.2022.00103

Zhang, S., Hu, Z., Zhu, G., Jin, M., & Li, K. C. (2021). Sentiment classification model based on semantic enhancement. Soft Computing, 25(1), 463–476. https://doi.org/10.1007/s00500-020-05160-8

Zhang, Y., Taft, M., Tang, J., & Li, L. (2024). Neural correlates of semantic-driven syntactic parsing in sentence comprehension. NeuroImage, 291, 120593. https://doi.org/10.1016/j.neuroimage.2024.120593

Zhu, Y. A., & Grüter, T. (2025). Native speakers and learners of Mandarin predict upcoming arguments in dative constructions based on categorical and gradient verb constraints. Bilingualism: Language and Cognition, 28(3), 601–612

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Copyright (c) 2026 Sun Jiaze, Mulyadi; Arga Lubis

Downloads

Download data is not yet available.