• Corpus ID: 16114296

Dependency Length Minimization: Puzzles and Promises

  title={Dependency Length Minimization: Puzzles and Promises},
  author={Haitao Liu and Chunshan Xu and Junying Liang},
In the recent issue of PNAS, Futrell et al. claims that their study of 37 languages gives the first large scale cross-language evidence for Dependency Length Minimization, which is an overstatement that ignores similar previous researches. In addition,this study seems to pay no attention to factors like the uniformity of genres,which weakens the validity of the argument that DLM is universal. Another problem is that this study sets the baseline random language as projective, which fails to… 

Response to Liu, Xu, and Liang (2015) and Ferrer-i-Cancho and Gómez-Rodríguez (2015) on Dependency Length Minimization

This work argues that its work provides novel, strong evidence for dependency length minimization as a universal quantitative property of languages, beyond this previous work, because it provides baselines which focus on word order preferences.

Normalized Dependency Distance: Proposing a New Measure

Analysis showed that exponential distribution fit well the distribution model of NDD as it did with Mean Dependency Distance, the algorithm used in previous studies, which suggests that the new algorithm may have, to some extent, addressed the issue of MDD’s dependency on sentence length.

A computational model for measuring discourse complexity

In past studies, the few quantitative approaches to discourse structure were mostly confined to the presentation of the frequency of discourse relations. However, quantitative approaches should take

Liberating Language Research from Dogmas of the 20th Century

A commentary on the article "Large-scale evidence of dependency length minimization in 37 languages" by Futrell, Mahowald & Gibson (PNAS 2015 112 (33) 10336-10341).

A Quantitative Analysis of English Compounds in Scientific Texts

The given research focuses on a statistical analysis of English compounds in the scientific texts with a special emphasis on the parts of speech and the cohesion of the constituents. In order to

Dependency distance minimization: a diachronic exploration of the effects of sentence length and dependency types

Dependency distance is regarded as an index of memory load and a measure of syntactic difficulty. Previous research has found that dependency distance tends to minimize both synchronically and



Large-scale evidence of dependency length minimization in 37 languages

Using parsed corpora of 37 diverse languages, it is shown that overall dependency lengths for all languages are shorter than conservative random baselines, suggesting that dependency length minimization is a universal quantitative property of human languages.

Do Grammars Minimize Dependency Length?

A well-established principle of language is that there is a preference for closely related words to be close together in the sentence. This can be expressed as a preference for dependency length

The risks of mixing dependency lengths from sequences of different length

Differences in the global averages of dependency length (mixing lengths from sentences of varying length) for two different languages do not simply imply a priori that one language optimizes dependency lengths better than the other because those differences could be due to differences in the distribution of sentence lengths and other factors.

The placement of the head that minimizes online memory: a complex systems approach

This study shows that the online memory cost is minimized when the head is placed at the center, regardless of the function that transforms length into cost, provided only that this function is strictly monotonically increasing.

Dependency Distance as a Metric of Language Comprehension Difficulty

The findings-that average dependency distance has a tendency to be minimized in human language and that there is a threshold of less than 3 words in average dependencydistance and grammar plays an important role in constraining distance-support all three hypotheses, although some questions are still open for further research.

Hubiness, length, crossings and their relationships in dependency trees

These findings suggest that the online memory cost of a sentence might be determined not just by the ordering of words but also by the hubiness of the underlying structure.

Quantitative typological analysis of Romance languages

The study shows that the distributions of dependency directions are suggestive of positive answers to the following two questions: whether quantitative methods and indexes can point to the diachronic syntactic drifts characterizing the evolution from Latin to Romance languages and whether these methods and index can provide evidence to evince the shared syntactic features among Romance languages.

Probability distribution of dependency distance

The fitting results reveal that the investigated distribu- tion can be well captured by the right truncated Zeta distribution and this model can be restricted only to natural language.

Euclidean distance between syntactically linked words.

  • R. Ferrer i Cancho
  • Computer Science
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2004
The Euclidean distance between syntactically linked words in sentences predicts, under ideal conditions, an exponential distribution of the distance between linked words, a trend that can be identified in real sentences.