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Neural Scoring Function for MST Parser

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10335489" target="_blank" >RIV/00216208:11320/16:10335489 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Neural Scoring Function for MST Parser

  • Original language description

    Continuous word representations appeared to be a useful feature in many natural language processing tasks. Using fixed-dimension pre-trained word embeddings allows avoiding sparse bag-of-words representation and to train models with fewer parameters. In this paper, we use fixed pre-trained word embeddings as additional features for a neural scoring function in the MST parser. With the multi-layer architecture of the scoring function we can avoid handcrafting feature conjunctions. The continuous word representations on the input also allow us to reduce the number of lexical features, make the parser more robust to out-of-vocabulary words, and reduce the total number of parameters of the model. Although its accuracy stays below the state of the art, the model size is substantially smaller than with the standard features set. Moreover, it performs well for languages where only a smaller treebank is available and the results promise to be useful in cross-lingual parsing.

  • 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)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • 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 10th International Conference on Language Resources and Evaluation (LREC 2016)

  • ISBN

    978-2-9517408-9-1

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    694-698

  • Publisher name

    European Language Resources Association

  • Place of publication

    Paris, France

  • Event location

    Portorož, Slovenia

  • Event date

    May 23, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article