Combining Dependency Parsers Using Error Rates

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11210%2F16%3A10330240" target="_blank" >RIV/00216208:11210/16:10330240 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-45510-5_10" target="_blank" >http://dx.doi.org/10.1007/978-3-319-45510-5_10</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-45510-5_10" target="_blank" >10.1007/978-3-319-45510-5_10</a>

Result language
angličtina
Original language name
Combining Dependency Parsers Using Error Rates
Original language description
This paper presents a method of improving dependency parsing accuracy by combining four parsers using error-rates (accuracy rates). We use four parsers: MSTParser, MaltParser, TurboParser and MateParser, and the data of the analytical layer of Prague Dependency Treebank. We parse data with each of the parsers and calculate error-rates for several parameters such as POS of the dependent token. These error-rates are then used to determine weights of edges in an oriented graph created by merging all the parses of a sentence provided by the parsers. We find a maximum spanning tree in this graph (a dependency tree without cycles), and achieve this way a 1.3 % UAS / 1.1 % LAS improvement compared to the best parser in our experiment.
Czech name
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Czech description
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Project
<a href="/en/project/LM2011023" target="_blank" >LM2011023: Czech National Corpus</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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