Minimization of dependency length in written English

Temperley, David

doi:10.1016/j.cognition.2006.09.011

Cited by 106 publications

(108 citation statements)

References 19 publications

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“…In combination with the preference for given-new ordering, we might then expect a cross-linguistic preference for orderings in which the object follows the subject, and this has in fact been observed: The three most common orderings of subject/verb/object-V-S-O, S-O-V, and S-V-O-all place the object after the subject (Dryer, 2005). As noted earlier, it has also been observed that object phrases tend to be longer than subject phrases, at least in English (Temperley, 2007); no doubt this is partly due to the much stronger tendency of subject phrases to be given rather than new.…”

Section: Discussionmentioning

confidence: 85%

Do Grammars Minimize Dependency Length?

2010

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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 minimization (DLM). In this study, we explore quantitatively the degree to which natural languages reflect DLM. We extract the dependencies from natural language text and reorder the words in such a way as to minimize dependency length. Comparing the original text with these optimal linearizations (and also with random linearizations) reveals the degree to which natural language minimizes dependency length. Tests on English data show that English shows a strong effect of DLM, with dependency length much closer to optimal than to random; the optimal English grammar also has many specific features in common with English. In German, too, dependency length is significantly less than random, but the effect is much weaker than in English. We conclude by speculating about some possible reasons for this difference between English and German.

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Section: Discussionmentioning

confidence: 85%

Do Grammars Minimize Dependency Length?

2010

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“…In availability models, speakers favour sentence structures where more readily available words are placed earlier, to reduce the need of holding already-retrieved information in memory and to start producing early (Bock & Irwin, 1980;Bock & Warren, 1985;Branigan, Pickering, & Tanaka, 2008;Bresnan et al, 2007;Ferreira & Dell, 2000;Ferreira & Yoshita, 2003;Levelt & Maassen, 1981;Prat-Sala & Branigan, 2000;Tanaka, Branigan, McLean, & Pickering, 2011;see Jaeger & Norcliffe, 2009, for an overview). In contrast, efficiency-based theories argue that the parser prefers word orders that allow the fastest computation of constituent structure (Hawkins, 1994(Hawkins, , 2014Temperley, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…This preference to produce shorter phrases before longer ones should hold regardless of the typological properties of the languages involved. Indeed, the tendency to shift long constituents over short ones (often known as heavy-NP shift) is widely attested in corpora studies in VO languages like English, German 3 , Hungarian, Greek, Polish, Finnish, Rumanian and Russian (de Marneffe, Grimm, Arnon, Kirby, & Bresnan, 2012;Hawkins, 1994;Hoffman, 1999;Kizach, 2012;Köhler, 1999;Lohse, Hawkins, & Wasow, 2004;Temperley, 2007;Uszkoreit, 1987;Uszkoreit et al, 1998;Wasow, 2002;Wiechmann & Lohmann, 2013; for an overview, see Jaeger & Norcliffe, 2009). There is also evidence from language production experiments supporting a short-before-long preference in English (Arnold et al, 2000;Marblestone, 2007;Stallings et al, 1998;Stallings & MacDonald, 2011).…”

Section: Availability-based Modelsmentioning

confidence: 99%

Aiming at shorter dependencies: the role of agreement morphology

Ros

Santesteban

Fukumura

et al. 2015

Language, Cognition and Neuroscience

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This study examined word order preferences as a function of phrasal length in Basque. Basque is an OV-language with flexible sentence word order and rich verb agreement. Contrary to the universal short-before-long preference predicted by availability models, Hawkins has argued that short-before-long orders are preferred in VO-languages such as English, whereas long-beforeshort orders are preferred in OV-languages such as Japanese (Hawkins, 2004). However, it is unclear how length affects word order preferences when an OV-language has rich verb agreement and allows postverbal arguments. We found a general long-before-short preference, and a tendency to place the verb in a sentence-medial position when one constituent is long. We argue that since agreement morphology signals the thematic role and case of surrounding phrases, it contributes to speeding up sentence processing. We conclude that morphologically rich languages employ both general adjacency mechanisms and language-specific resources to enhance language efficiency.

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“…These principles have been blamed for several linguistic phenomena across languages, both by traditional linguists (Hawkins, 1994) and by computational linguists (Gildea and Temperley, 2007;Temperley, 2007). For example, (1) helps explain the "late closure" or "attach low" heuristic, whereby a modifier such as a PP is more likely to attach to the closest appropriate head (Frazier, 1979;Hobbs and Bear, 1990, for example).…”

Section: Short Dependencies In Langugagementioning

confidence: 99%

Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length

Eisner

Smith

2010

Text, Speech and Language Technology

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In lexicalized phrase-structure or dependency parses, a word's modifiers tend to fall near it in the string. This fact can be exploited by parsers. We first show that a crude way to use dependency length as a parsing feature can substantially improve parsing speed and accuracy in English and Chinese, with more mixed results on German. We then show similar improvements by imposing hard bounds on dependency length and (additionally) modeling the resulting sequence of parse fragments. The approach with hard bounds, "vine grammar," accepts only a regular language, even though it happily retains a context-free parameterization and defines meaningful parse trees. We show how to parse this language in O(n) time, using a novel chart parsing algorithm with a low grammar constant (rather than an impractically large finite-state recognizer with an exponential grammar constant).

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Minimization of dependency length in written English

Cited by 106 publications

References 19 publications

Do Grammars Minimize Dependency Length?

Do Grammars Minimize Dependency Length?

Aiming at shorter dependencies: the role of agreement morphology

Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length

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