Anti dependency distance minimization in short sequences. A graph theoretic approach
This addresses a theoretical prediction in linguistics about word order principles in short sequences, though it is incremental as it tests an existing hypothesis.
The study tackled the problem of whether dependency distance minimization (DDm) holds in short sentences, finding anti-DDm in some languages, with evidence from syntactic dependency structures.
Dependency distance minimization (DDm) is a word order principle favouring the placement of syntactically related words close to each other in sentences. Massive evidence of the principle has been reported for more than a decade with the help of syntactic dependency treebanks where long sentences abound. However, it has been predicted theoretically that the principle is more likely to be beaten in short sequences by the principle of surprisal minimization (predictability maximization). Here we introduce a simple binomial test to verify such a hypothesis. In short sentences, we find anti-DDm for some languages from different families. Our analysis of the syntactic dependency structures suggests that anti-DDm is produced by star trees.