Menzerath's Law in the Syntax of Languages Compared with Random Sentences

Area of Science:

• Linguistics
• Computational Linguistics
• Natural Language Processing

Background:

• The Menzerath law posits an inverse relationship between the size of a linguistic unit and the number of constructs it contains.
• Previous research indicated the Menzerath law's applicability to dependency corpora in languages like Czech and Ukrainian.
• Syntactic complexity in natural language is a key area of linguistic research.

Purpose of the Study:

• To investigate the syntactic application of the Menzerath law across a wide range of languages.
• To determine if the Menzerath law's properties hold consistently in diverse linguistic structures.
• To compare the Menzerath law's behavior in natural language syntax versus syntactically randomized data.

Main Methods:

• Utilized the Universal Dependency dataset (version 2.3), encompassing 76 languages and 129 corpora.
• Analyzed the Penn Treebank (PTB) dataset for syntactic properties.
• Generated and analyzed syntactically randomized sentences from the PTB for comparative purposes.

Main Results:

• The Menzerath law was found to hold reasonably well for sentences with more than two modifying constituents (x>2).
• The observed patterns of the Menzerath law were found to be highly reproducible even in syntactically randomized sentence structures.
• Cross-linguistic analysis confirmed the general applicability of the Menzerath law in syntactic structures.

Conclusions:

• The Menzerath law demonstrates a consistent, albeit sometimes weak, pattern in syntactic structures across numerous languages.
• The reproducibility of the Menzerath law in randomized data suggests that simple statistical properties may underlie some aspects of linguistic complexity.
• Further analysis is warranted to explore the nuanced characteristics of natural language complexity illuminated by the Menzerath law.