eBook: Paradigm Structure and Predictability in Latin Inflection: An Entropy-based Approach (DRM PDF)
 
電子書格式: DRM PDF
作者: Matteo Pellegrini 
系列: Studies in Morphology
分類: Historical & comparative linguistics ,
Grammar, syntax & morphology ,
Computational linguistics  
書城編號: 27149061


售價: $1294.00

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製造商: Springer International Publishing
出版日期: 2023/03/31
ISBN: 9783031248443
 
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商品簡介
Latin paradigms are almost proverbially known, and they have often been used as a test case for different theoretical approaches to morphological complexity. This book analyses them in a completely word-based perspective, using a recently developed information-theoretic methodology, making entropy-based techniques of analysis available to a wider readership. By doing so, it shows the relevance of traditional notions like principal parts, giving them a more principled, data-driven formulation. Furthermore, it suggests enhancements to the standard information-theoretic methodology, allowing to account for the role of external factors - like gender and derivational information - in improving predictability between inflected word forms. This book is useful to morphologists, that will see ideas and techniques taken from the current debate on morphological theory tested on complex phenomena of a language as renowned as Latin. It is also helpful for scholars working in both Latin and Romance linguistics: the former will find a freely available lexical resource and a novel description of Latin paradigms, that can be exploited by the latter to draw a comparison with recent analyses of the inflectional morphology of several Romance languages.
Studies in Morphology

eBook: Paradigm Structure and Predictability in Latin Inflection: An Entropy-based Approach (DRM PDF)

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Matteo Pellegrini 作者作品表

eBook: Paradigm Structure and Predictability in Latin Inflection: An Entropy-based Approach (DRM PDF)

eBook: Paradigm Structure and Predictability in Latin Inflection: An Entropy-based Approach (DRM EPUB)

Paradigm Structure and Predictability in Latin Inflection: An Entropy-Based Approach (2023) (Hardcover)

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