Combining Diverse Word-Alignment Symmetrizations Improves Dependency Tree Projection

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F11%3A10107816" target="_blank" >RIV/00216208:11320/11:10107816 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-19400-9" target="_blank" >http://dx.doi.org/10.1007/978-3-642-19400-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-19400-9" target="_blank" >10.1007/978-3-642-19400-9</a>

Result language
angličtina
Original language name
Combining Diverse Word-Alignment Symmetrizations Improves Dependency Tree Projection
Original language description
For many languages, we are not able to train any supervised parser, because there are no manually annotated data available. This problem can be solved by using a parallel corpus with English, parsing the English side, projecting the dependencies throughword-alignment connections, and training a parser on the projected trees. In this paper, we introduce a simple algorithm using a combination of various word-alignment symmetrizations. We prove that our method outperforms previous work, even though it uses McDonald's maximum-spanning-tree parser as it is, without any "unsupervised" modifications.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AI - Linguistics
OECD FORD branch
—

Project
<a href="/en/project/GD201%2F09%2FH057" target="_blank" >GD201/09/H057: Res Informatica</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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