Abstract
This paper gives an overview of results of automatic analysis of word order in 23 dependency treebanks. These treebanks have been collected in the frame of the HamleDT project, whose main goal is to provide universal annotation for dependency corpora; thus it also makes it possible to use identical queries for all the corpora. The analysis concentrates on basic characteristics of word order, the order of three main constituents, a predicate, a subject and an object. A quantitative analysis is performed separately for main clauses and subordinated clauses; further, a presence of an active verb is taken into account – we show that in many languages the subordinated clauses have a slightly different order of words than main clauses; the choice of voice has also an impact on word order.
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Notes
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Data of each treebank in HamleDT are distributed in three annotation schemes – (a) the transformation of the treebank to the praguian style (used in PDT; leftmost in Fig. 1), (b) the original annotation format of the given treebank (or its dependency transformation in case of non-dependency treebanks; in the middle of Fig. 1), and (c) the transformation of the treebank to the Universal Dependencies style (rigthmost in the figure).
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In this experiment, we do not distinguish among various sources of incompleteness as e.g. those caused by imperatives, intransitives, pro-drop subjects or objects etc.
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The apparent explanation based on a strong pro-drop nature of Japanese seems to be too simplistic as other languages exhibiting the same property (like e.g. Czech) do not show any similar reduction of the number of filtered sentences.
References
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Acknowledgments
This work has been using language resources and tools developed, stored, and distributed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).
The work on this project has been partially supported by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071).
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Kuboň, V., Lopatková, M., Mírovský, J. (2018). Analysis of Word Order in Multiple Treebanks. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2016. Lecture Notes in Computer Science(), vol 9623. Springer, Cham. https://doi.org/10.1007/978-3-319-75477-2_24
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