<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="federmann-2018-appraise">
    <titleInfo>
        <title>Appraise Evaluation Framework for Machine Translation</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Christian</namePart>
        <namePart type="family">Federmann</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Dongyan</namePart>
            <namePart type="family">Zhao</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Santa Fe, New Mexico</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We present Appraise, an open-source framework for crowd-based annotation tasks, notably for evaluation of machine translation output. This is the software used to run the yearly evaluation campaigns for shared tasks at the WMT Conference on Machine Translation. It has also been used at IWSLT 2017 and, recently, to measure human parity for machine translation for Chinese to English news text. The demo will present the full end-to-end lifecycle of an Appraise evaluation campaign, from task creation to annotation and interpretation of results.</abstract>
    <identifier type="citekey">federmann-2018-appraise</identifier>
    <location>
        <url>https://aclanthology.org/C18-2019</url>
    </location>
    <part>
        <date>2018-08</date>
        <extent unit="page">
            <start>86</start>
            <end>88</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Appraise Evaluation Framework for Machine Translation
%A Federmann, Christian
%Y Zhao, Dongyan
%S Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico
%F federmann-2018-appraise
%X We present Appraise, an open-source framework for crowd-based annotation tasks, notably for evaluation of machine translation output. This is the software used to run the yearly evaluation campaigns for shared tasks at the WMT Conference on Machine Translation. It has also been used at IWSLT 2017 and, recently, to measure human parity for machine translation for Chinese to English news text. The demo will present the full end-to-end lifecycle of an Appraise evaluation campaign, from task creation to annotation and interpretation of results.
%U https://aclanthology.org/C18-2019
%P 86-88

Markdown (Informal)

[Appraise Evaluation Framework for Machine Translation](https://aclanthology.org/C18-2019) (Federmann, COLING 2018)

• Appraise Evaluation Framework for Machine Translation (Federmann, COLING 2018)

ACL

• Christian Federmann. 2018. Appraise Evaluation Framework for Machine Translation. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 86–88, Santa Fe, New Mexico. Association for Computational Linguistics.