Do dependency lengths explain constraints on crossing dependencies?

Abstract

In syntactic dependency trees, when arcs are drawn from syntactic heads to dependents, they rarely cross. Constraints on these crossing dependencies are critical for determining the syntactic properties of human language, because they define the position of natural language in formal language hierarchies. We study whether the apparent constraints on crossing syntactic dependencies in natural language might be explained by constraints on dependency lengths (the linear distance between heads and dependents). We compare real dependency trees from treebanks of 52 languages against baselines of random trees which are matched with the real trees in terms of their dependency lengths. We find that these baseline trees have many more crossing dependencies than real trees, indicating that a constraint on dependency lengths alone cannot explain the empirical rarity of crossing dependencies. However, we find evidence that a combined constraint on dependency length and the rate of crossing dependencies might be able to explain two of the most-studied formal restrictions on dependency trees: gap degree and well-nestedness.

Assessing Corpus Evidence for Formal and Psycholinguistic Constraints on Nonprojectivity

“…An interesting result that should be interpreted in the light of previous findings is the effect of dependency lengths on the occurrence of crossing dependencies. Recent work has shown that a constraint on dependency length alone cannot fully explain the low rate of crossing dependencies in natural languages (Yadav, Husain, and Futrell 2021). In contrast, our results show an effect of dependency length on crossing tendency such that longer dependencies are more likely to cross -or get crossed by -other dependencies.…”

“…The resulting distribution is uniform over all tree structures with the specified length and number of crossing edges. A DL-controlled random tree must match a real tree both in terms of its number of crossings and in terms of the distribution of dependency lengths within the tree (for details, see Yadav, Husain, and Futrell 2021). This procedure samples from the uniform distribution on trees with specified length, number of crossings, and distribution of dependency lengths.…”

“…Tree topology Dependency length Random trees RLAs DL-controlled random trees DL-controlled RLAs details, see Yadav, Husain, and Futrell 2021). This procedure samples from the uniform distribution on trees with specified length, number of crossings, and distribution of dependency lengths.…”

Memory limitations are hidden in grammar

“…Whereas a recent study of similar classes of grammars suggested that crossing dependencies are constrained by either grammar or cognitive pressures rather than occurring naturally at some rate (Yadav et al, 2019), our findings strongly demonstrate that it is not grammar but rather non-linguistic cognitive constraints, that limit the occurrence of crossing dependencies in languages. Since we released the first version of this article in August 2019, https://arxiv.org/abs/1908.06629, other researchers have confirmed that dependency distance minimiza-tion contributes significantly to the emergence of formal constraints on crossing dependencies (Yadav et al, 2021(Yadav et al, , 2022. Yadav et al, 2021 have also confirmed the findings of previous research indicating that the effect of dependency distances alone leads to overestimate the actual number of crossing dependencies (Gómez-Rodríguez and Ferrer-i-Cancho, 2017); a critical point is that Gómez-Rodríguez and Ferrer-i-Cancho (2017) use a normalized score leading to the conclusion that such overestimation implies a small relative error.…”

“…Since we released the first version of this article in August 2019, https://arxiv.org/abs/1908.06629, other researchers have confirmed that dependency distance minimiza-tion contributes significantly to the emergence of formal constraints on crossing dependencies (Yadav et al, 2021(Yadav et al, , 2022. Yadav et al, 2021 have also confirmed the findings of previous research indicating that the effect of dependency distances alone leads to overestimate the actual number of crossing dependencies (Gómez-Rodríguez and Ferrer-i-Cancho, 2017); a critical point is that Gómez-Rodríguez and Ferrer-i-Cancho (2017) use a normalized score leading to the conclusion that such overestimation implies a small relative error.…”