CLNov 26, 2022

The distribution of syntactic dependency distances

arXiv:2211.14620v34 citationsh-index: 31
Originality Incremental advance
AI Analysis

This research addresses a fundamental problem in linguistics and natural language processing by revealing cross-linguistic patterns in syntactic processing, though it is incremental as it builds on prior work on dependency distances.

The study tackled the problem of characterizing the distribution of syntactic dependency distances in sentences, finding that a two-regime model with a break-point at 4-5 words is most likely across 20 languages, indicating a universal chunk-and-pass mechanism.

The syntactic structure of a sentence can be represented as a graph, where vertices are words and edges indicate syntactic dependencies between them. In this setting, the distance between two linked words is defined as the difference between their positions. Here we wish to contribute to the characterization of the actual distribution of syntactic dependency distances, which has previously been argued to follow a power-law distribution. Here we propose a new model with two exponential regimes in which the probability decay is allowed to change after a break-point. This transition could mirror the transition from the processing of word chunks to higher-level structures. We find that a two-regime model - where the first regime follows either an exponential or a power-law decay - is the most likely one in all 20 languages we considered, independently of sentence length and annotation style. Moreover, the break-point exhibits low variation across languages and averages values of 4-5 words, suggesting that the amount of words that can be simultaneously processed abstracts from the specific language to a high degree. The probability decay slows down after the breakpoint, consistently with a universal chunk-and-pass mechanism. Finally, we give an account of the relation between the best estimated model and the closeness of syntactic dependencies as function of sentence length, according to a recently introduced optimality score.

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