SUD or Surface-Syntactic Universal Dependencies: An annotation scheme near-isomorphic to UD

Gerdes, Kim; Guillaume, Bruno; Kahane, Sylvain; Perrier, Guy

doi:10.18653/v1/w18-6008

Cited by 56 publications

(73 citation statements)

References 7 publications

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“…To expand on this work we would also like to see how the observed properties and the relations between them are affected by the annotation scheme, in particular contrasting schemas where content words are governors (as is the case in UD) and schemas where function words are governors (for example using the SUD schema proposed by Gerdes et al (2018)), as it will have an impact on height, dependency distances, and the types of configurations that can be extracted from the treebanks.…”

Section: Resultsmentioning

confidence: 99%

“…This makes PUD a good choice for future studies which would further test whether our finding here can be generalized into different human languages. We use the Surface-syntactic UD version of the treebank (Gerdes et al, 2018), which is more suitable for studies in distributional dependency syntax as it corrects the artificially long dependency distances of UD into a more standard syntactic analysis based on distributional criteria (Osborne & .…”

Section: Methodsmentioning

confidence: 99%

“…It aims to make the annotation scheme close to the dependency traditions, like Meaning-Text-Theory (MTT) , Word Grammar (Hudson, 1984), etc. Hence, the SUD annotation scheme is a syntactic-oriented dependency representation that seeks to promote the syntactic motivations (Gerdes et al, 2018;Osborne and Gerdes, 2019). Therefore, the UD and SUD annotation schemes signify two typical preferences of dependency grammar, one is semantic-oriented, and the other is syntactic-oriented.…”

Section: Background and Motivationmentioning

confidence: 99%

“…Since the SUD annotation scheme is near-isomorphic to the UD initiative (Gerdes et al, 2018), treebanks based on UD and SUD are very similar to a large extent. The greatest difference between UD and SUD treebanks is the direction of the dependency types used to indicate the relations between function words and content words.…”

Section: Annotation Scheme and Annotating Preferencementioning

confidence: 99%

“…the comp relation between along and lake in Figure 1 (b)) (Gerdes et al, 2018: 71 are also altered. This shows that the underlying reason for the distinction between UD and SUD annotation scheme is that the UD annotation scheme favours taking the content words as the head of function words while the SUD annotation scheme chooses the function words as heads over content words in dependency relations Gerdes et al, 2018;Osborne and Gerdes, 2019). To be specific, the UD treebanks first connect the content words and then the function words to emphasize the semantic similarities of all languages, while the SUD treebanks connect content words mediated by function words to complete the functional roles of function words.…”

Section: Annotation Scheme and Annotating Preferencementioning

confidence: 99%

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Proceedings of the First Workshop on Quantitative Syntax (Quasy, SyntaxFest 2019)

2019

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The use of corpora for NLP and linguistics has only increased in recent years. In NLP, machine learning systems are by nature data-intensive, and in linguistics there is a renewed interest in the empirical validation of linguistic theory, particularly through corpus evidence. While the first statistical parsers have long been trained on the Penn treebank phrase structures, dependency treebanks, whether natively annotated with dependencies, or converted from phrase structures, have become more and more popular, as evidenced by the success of the Universal Dependency project, currently uniting 120 treebanks in 80 languages, annotated in the same dependency-based scheme. The availability of these resources has boosted empirical quantitative studies in syntax. It has also lead to a growing interest in theoretical questions around syntactic dependency, its history, its foundations, and the analyses of various constructions in dependency-based frameworks. Furthermore, the availability of large, multilingual annotated data sets, such as those provided by the Universal Dependencies project, has made cross-linguistic analysis possible to an extent that could only be dreamt of only a few years ago. In this context it was natural to bring together TLT (Treebanks and Linguistic Theories), the historical conference on treebanks as linguistic resources, Depling (The international conference on Dependency Linguistics), the conference uniting research on models and theories around dependency representations, and UDW (Universal Dependency Workshop), the annual meeting of the UD project itself. Moreover, in order to create a point of contact with the large community working in quantitative linguistics it seemed expedient to create a workshop dedicated to quantitative syntactic measures on treebanks and raw corpora, which gave rise to Quasy, the first workshop on Quantitative Syntax. And this led us to the first SyntaxFest. Because the potential audience and submissions to the four events were likely to have substantial overlap, we decided to have a single reviewing process for the whole SyntaxFest. Authors could choose to submit their paper to one or several of the four events, and in case of acceptance, the program co-chairs would decide which event to assign the accepted paper to.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Background and Motivationmentioning

confidence: 99%

Section: Annotation Scheme and Annotating Preferencementioning

confidence: 99%

Section: Annotation Scheme and Annotating Preferencementioning

confidence: 99%

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