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Improvements to Syntax-based Machine Translation using Ensemble Dependency Parsers

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F13%3A10194639" target="_blank" >RIV/00216208:11320/13:10194639 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Improvements to Syntax-based Machine Translation using Ensemble Dependency Parsers

  • Original language description

    Dependency parsers are almost ubiqui- tously evaluated on their accuracy scores, these scores say nothing of the complex- ity and usefulness of the resulting struc- tures. The structures may have more com- plexity due to their coordination structure or attachment rules. As dependency parses are basic structures in which other systems are built upon, it would seem more reason- able to judge these parsers down the NLP pipeline. We show results from 7 individual parsers, including dependency and constituent parsers, and 3 ensemble parsing tech- niques with their overall effect on a Ma- chine Translation system, Treex, for En- glish to Czech translation. We show that parsers' UAS scores are more correlated to the NIST evaluation metric than to the BLEU Metric, however we see increases in both metrics.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/LM2010013" target="_blank" >LM2010013: LINDAT-CLARIN: Institute for analysis, processing and distribution of linguistic data</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Second Workshop on Hybrid Approaches to Translation

  • ISBN

    978-1-937284-63-3

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    19-24

  • Publisher name

    Omnipress, Inc.

  • Place of publication

    Sofija, Bulgaria

  • Event location

    Sofija, Bulgaria

  • Event date

    Aug 8, 2013

  • Type of event by nationality

    CST - Celostátní akce

  • UT code for WoS article