Hexatagging: Projective Dependency Parsing as Tagging
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3ARCYERS9H" target="_blank" >RIV/00216208:11320/23:RCYERS9H - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162617099&partnerID=40&md5=f34fe0093a22a6959901c206239f5289" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162617099&partnerID=40&md5=f34fe0093a22a6959901c206239f5289</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Hexatagging: Projective Dependency Parsing as Tagging
Original language description
"We introduce a novel dependency parser, the hexatagger, that constructs dependency trees by tagging the words in a sentence with elements from a finite set of possible tags. In contrast to many approaches to dependency parsing, our approach is fully parallelizable at training time, i.e., the structure-building actions needed to build a dependency parse can be predicted in parallel to each other. Additionally, exact decoding is linear in time and space complexity. Furthermore, we derive a probabilistic dependency parser that predicts hexatags using no more than a linear model with features from a pretrained language model, i.e., we forsake a bespoke architecture explicitly designed for the task. Despite the generality and simplicity of our approach, we achieve state-of-the-art performance of 96.4 LAS and 97.4 UAS on the Penn Treebank test set. Additionally, our parser’s linear time complexity and parallelism significantly improve computational efficiency, with a roughly 10-times speed-up over previous state-of-the-art models during decoding. © 2023 Association for Computational Linguistics."
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
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Proc. Annu. Meet. Assoc. Comput Linguist."
ISBN
978-195942971-5
ISSN
0736-587X
e-ISSN
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Number of pages
12
Pages from-to
1453-1464
Publisher name
Association for Computational Linguistics (ACL)
Place of publication
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Event location
Melaka, Malaysia
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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