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        <title>Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation</title>
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        <namePart type="given">Simon</namePart>
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        <namePart type="family">Belz</namePart>
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    <name type="personal">
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            <title>Proceedings of the 11th International Conference on Natural Language Generation</title>
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    <abstract>In this paper, we present the datasets used in the Shallow and Deep Tracks of the First Multilingual Surface Realisation Shared Task (SR’18). For the Shallow Track, data in ten languages has been released: Arabic, Czech, Dutch, English, Finnish, French, Italian, Portuguese, Russian and Spanish. For the Deep Track, data in three languages is made available: English, French and Spanish. We describe in detail how the datasets were derived from the Universal Dependencies V2.0, and report on an evaluation of the Deep Track input quality. In addition, we examine the motivation for, and likely usefulness of, deriving NLG inputs from annotations in resources originally developed for Natural Language Understanding (NLU), and assess whether the resulting inputs supply enough information of the right kind for the final stage in the NLG process.</abstract>
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    <identifier type="doi">10.18653/v1/W18-6527</identifier>
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        <date>2018-11</date>
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%0 Conference Proceedings
%T Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation
%A Mille, Simon
%A Belz, Anja
%A Bohnet, Bernd
%A Wanner, Leo
%Y Krahmer, Emiel
%Y Gatt, Albert
%Y Goudbeek, Martijn
%S Proceedings of the 11th International Conference on Natural Language Generation
%D 2018
%8 November
%I Association for Computational Linguistics
%C Tilburg University, The Netherlands
%F mille-etal-2018-underspecified
%X In this paper, we present the datasets used in the Shallow and Deep Tracks of the First Multilingual Surface Realisation Shared Task (SR’18). For the Shallow Track, data in ten languages has been released: Arabic, Czech, Dutch, English, Finnish, French, Italian, Portuguese, Russian and Spanish. For the Deep Track, data in three languages is made available: English, French and Spanish. We describe in detail how the datasets were derived from the Universal Dependencies V2.0, and report on an evaluation of the Deep Track input quality. In addition, we examine the motivation for, and likely usefulness of, deriving NLG inputs from annotations in resources originally developed for Natural Language Understanding (NLU), and assess whether the resulting inputs supply enough information of the right kind for the final stage in the NLG process.
%R 10.18653/v1/W18-6527
%U https://aclanthology.org/W18-6527
%U https://doi.org/10.18653/v1/W18-6527
%P 199-209

Markdown (Informal)

[Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation](https://aclanthology.org/W18-6527) (Mille et al., INLG 2018)

• Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation (Mille et al., INLG 2018)

ACL

• Simon Mille, Anja Belz, Bernd Bohnet, and Leo Wanner. 2018. Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation. In Proceedings of the 11th International Conference on Natural Language Generation, pages 199–209, Tilburg University, The Netherlands. Association for Computational Linguistics.