Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10130050" target="_blank" >RIV/00216208:11320/12:10130050 - isvavai.cz</a>
Result on the web
<a href="http://www.aclweb.org/anthology/W/W12/W12-0503" target="_blank" >http://www.aclweb.org/anthology/W/W12/W12-0503</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser
Original language description
Dependency parsing has made many advancements in recent years, in particular for English. There are a few dependency parsers that achieve comparable accuracy scores with each other but with very different types of errors. This paper examines creating a new dependency structure through ensemble learning using a hybrid of the outputs of various parsers. We combine all tree outputs into a weighted edge graph, using 4 weighting mechanisms. The weighted edge graph is the input into our ensemble system and isa hybrid of very different parsing techniques (constituent parsers, transition-based dependency parsers, and a graph-based parser). From this graph we take a maximum spanning tree. We examine the new dependency structure in terms of accuracy and errorson individual part-of-speech values. The results indicate that using a greater number of more varied parsers will improve accuracy results. The combined ensemble system, using 5 parsers based on 3 different parsing techniques, achieves an
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2012
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 Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
ISBN
978-1-937284-19-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
19-26
Publisher name
Association for Computational Linguistics
Place of publication
Avignon, France
Event location
Avignon, France
Event date
Apr 23, 2012
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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