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    <titleInfo>
        <title>Finding the “right” answers for customers</title>
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        <namePart type="given">Frank</namePart>
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            <title>Proceedings of the 10th International Conference on Natural Language Generation</title>
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            <namePart type="given">Jose</namePart>
            <namePart type="given">M</namePart>
            <namePart type="family">Alonso</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Alberto</namePart>
            <namePart type="family">Bugarín</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
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    <abstract>This talk will present a few NLG systems developed within Thomson Reuters providing information to professionals such as lawyers, accountants or traders. Based on the experience developing these system, I will discuss the usefulness of automatic metrics, crowd-sourced evaluation, corpora studies and expert reviews. I will conclude with exploring the question of whether developers of NLG systems need to follow ethical guidelines and how those guidelines could be established.</abstract>
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    <identifier type="doi">10.18653/v1/W17-3510</identifier>
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%0 Conference Proceedings
%T Finding the “right” answers for customers
%A Schilder, Frank
%Y Alonso, Jose M.
%Y Bugarín, Alberto
%Y Reiter, Ehud
%S Proceedings of the 10th International Conference on Natural Language Generation
%D 2017
%8 September
%I Association for Computational Linguistics
%C Santiago de Compostela, Spain
%F schilder-2017-finding
%X This talk will present a few NLG systems developed within Thomson Reuters providing information to professionals such as lawyers, accountants or traders. Based on the experience developing these system, I will discuss the usefulness of automatic metrics, crowd-sourced evaluation, corpora studies and expert reviews. I will conclude with exploring the question of whether developers of NLG systems need to follow ethical guidelines and how those guidelines could be established.
%R 10.18653/v1/W17-3510
%U https://aclanthology.org/W17-3510
%U https://doi.org/10.18653/v1/W17-3510
%P 74

Markdown (Informal)

[Finding the “right” answers for customers](https://aclanthology.org/W17-3510) (Schilder, INLG 2017)

• Finding the “right” answers for customers (Schilder, INLG 2017)

ACL

• Frank Schilder. 2017. Finding the “right” answers for customers. In Proceedings of the 10th International Conference on Natural Language Generation, page 74, Santiago de Compostela, Spain. Association for Computational Linguistics.