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        <title>Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach</title>
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    <name type="personal">
        <namePart type="given">Thiago</namePart>
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    <name type="personal">
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            <title>Proceedings of the First Workshop on Multilingual Surface Realisation</title>
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            <namePart type="given">Simon</namePart>
            <namePart type="family">Mille</namePart>
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        <name type="personal">
            <namePart type="given">Anja</namePart>
            <namePart type="family">Belz</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Bernd</namePart>
            <namePart type="family">Bohnet</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Emily</namePart>
            <namePart type="family">Pitler</namePart>
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        <name type="personal">
            <namePart type="given">Leo</namePart>
            <namePart type="family">Wanner</namePart>
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    <abstract>This study describes the approach developed by the Tilburg University team to the shallow task of the Multilingual Surface Realization Shared Task 2018 (SR18). Based on (Castro Ferreira et al., 2017), the approach works by first preprocessing an input dependency tree into an ordered linearized string, which is then realized using a statistical machine translation model. Our approach shows promising results, with BLEU scores above 50 for 5 different languages (English, French, Italian, Portuguese and Spanish) and above 35 for the Dutch language.</abstract>
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    <identifier type="doi">10.18653/v1/W18-3604</identifier>
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%0 Conference Proceedings
%T Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach
%A Castro Ferreira, Thiago
%A Wubben, Sander
%A Krahmer, Emiel
%Y Mille, Simon
%Y Belz, Anja
%Y Bohnet, Bernd
%Y Pitler, Emily
%Y Wanner, Leo
%S Proceedings of the First Workshop on Multilingual Surface Realisation
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F castro-ferreira-etal-2018-surface
%X This study describes the approach developed by the Tilburg University team to the shallow task of the Multilingual Surface Realization Shared Task 2018 (SR18). Based on (Castro Ferreira et al., 2017), the approach works by first preprocessing an input dependency tree into an ordered linearized string, which is then realized using a statistical machine translation model. Our approach shows promising results, with BLEU scores above 50 for 5 different languages (English, French, Italian, Portuguese and Spanish) and above 35 for the Dutch language.
%R 10.18653/v1/W18-3604
%U https://aclanthology.org/W18-3604
%U https://doi.org/10.18653/v1/W18-3604
%P 35-38

Markdown (Informal)

[Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach](https://aclanthology.org/W18-3604) (Castro Ferreira et al., ACL 2018)

• Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach (Castro Ferreira et al., ACL 2018)

ACL

• Thiago Castro Ferreira, Sander Wubben, and Emiel Krahmer. 2018. Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach. In Proceedings of the First Workshop on Multilingual Surface Realisation, pages 35–38, Melbourne, Australia. Association for Computational Linguistics.