Inferring morphological complexity from syntactic dependency networks: a test

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Abstract

Research in linguistic typology has shown that languages do not fall into the neat morphological types (synthetic vs. analytic) postulated in the 19th century. Instead, analytic and synthetic must be viewed as two poles of a continuum and languages may show a mix analytic and synthetic strategies to different degrees. Unfortunately, empirical studies that offer a more fine-grained morphological classification of languages based on these parameters remain few. In this paper, we build upon previous research by Liu & Xu (2011) and investigate the possibility of inferring information on morphological complexity from syntactic dependency networks.

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APA

Villa, L. B., & Inglese, G. (2021). Inferring morphological complexity from syntactic dependency networks: a test. In SIGTYP 2021 - 3rd Workshop on Research in Computational Typology and Multilingual NLP, Proceedings of the Workshop (pp. 10–22). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.sigtyp-1.2

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