Tweaking UD Annotations to Investigate the Placement of Determiners, Quantifiers and Numerals in the Noun Phrase
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3AIN5JQ54I" target="_blank" >RIV/00216208:11320/22:IN5JQ54I - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2022.sigtyp-1.5" target="_blank" >https://aclanthology.org/2022.sigtyp-1.5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2022.sigtyp-1.5" target="_blank" >10.18653/v1/2022.sigtyp-1.5</a>
Alternative languages
Result language
angličtina
Original language name
Tweaking UD Annotations to Investigate the Placement of Determiners, Quantifiers and Numerals in the Noun Phrase
Original language description
We describe a methodology to extract with finer accuracy word order patterns from texts automatically annotated with Universal Dependency (UD) trained parsers. We use the methodology to quantify the word order entropy of determiners, quantifiers and numerals in ten Indo-European languages, using UD-parsed texts from a parallel corpus of prosaic texts. Our results suggest that the combinations of different UD annotation layers, such as UD Relations, Universal Parts of Speech and lemma, and the introduction of language-specific lists of closed-category lemmata has the two-fold effect of improving the quality of analysis and unveiling hidden areas of variability in word order patterns.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP
ISBN
978-1-955917-93-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
36-41
Publisher name
Association for Computational Linguistics
Place of publication
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Event location
Seattle, Washington
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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