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Evaluating Natural Language Processing Tasks with Low Inter-Annotator Agreement: The Case of Corpus Applications

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00092356" target="_blank" >RIV/00216224:14330/16:00092356 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evaluating Natural Language Processing Tasks with Low Inter-Annotator Agreement: The Case of Corpus Applications

  • Original language description

    In Low inter-annotator agreement = an ill-defined problem?, we have argued that tasks with low inter-annotator agreement are really common in natural language processing (NLP) and they deserve an appropriate attention. We have also outlined a preliminary solution for their evaluation. In On evaluation of natural language processing tasks: Is gold standard evaluation methodology a good solution? , we have agitated for extrinsic application-based evaluation of NLP tasks and against the gold standard methodology which is currently almost the only one really used in the NLP field. This paper brings a synthesis of these two: For three practical tasks, that normally have so low inter-annotator agreement that they are considered almost irrelevant to any scentific evaluation, we introduce an application-based evaluation scenario which illustrates that it is not only possible to evaluate them in a scientific way, but that this type of evaluation is much more telling than the gold standard way.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/7F14047" target="_blank" >7F14047: Harvesting big text data for under-resourced languages</a><br>

  • Continuities

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

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

    Tenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2016

  • ISBN

    9788026310952

  • ISSN

    2336-4289

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    127-134

  • Publisher name

    Tribun EU

  • Place of publication

    Brno

  • Event location

    Karlova Studánka

  • Event date

    Jan 1, 2016

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article