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    <abstract>This paper presents results from the Third Shared Task on Multilingual Surface Realisation (SR’20) which was organised as part of the COLING’20 Workshop on Multilingual Surface Realisation. As in SR’18 and SR’19, the shared task comprised two tracks: (1) a Shallow Track where the inputs were full UD structures with word order information removed and tokens lemmatised; and (2) a Deep Track where additionally, functional words and morphological information were removed. Moreover, each track had two subtracks: (a) restricted-resource, where only the data provided or approved as part of a track could be used for training models, and (b) open-resource, where any data could be used. The Shallow Track was offered in 11 languages, whereas the Deep Track in 3 ones. Systems were evaluated using both automatic metrics and direct assessment by human evaluators in terms of Readability and Meaning Similarity to reference outputs. We present the evaluation results, along with descriptions of the SR’19 tracks, data and evaluation methods, as well as brief summaries of the participating systems. For full descriptions of the participating systems, please see the separate system reports elsewhere in this volume.</abstract>
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%0 Conference Proceedings
%T The Third Multilingual Surface Realisation Shared Task (SR’20): Overview and Evaluation Results
%A Mille, Simon
%A Belz, Anya
%A Bohnet, Bernd
%A Castro Ferreira, Thiago
%A Graham, Yvette
%A Wanner, Leo
%Y Belz, Anya
%Y Bohnet, Bernd
%Y Ferreira, Thiago Castro
%Y Graham, Yvette
%Y Mille, Simon
%Y Wanner, Leo
%S Proceedings of the Third Workshop on Multilingual Surface Realisation
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain (Online)
%F mille-etal-2020-third
%X This paper presents results from the Third Shared Task on Multilingual Surface Realisation (SR’20) which was organised as part of the COLING’20 Workshop on Multilingual Surface Realisation. As in SR’18 and SR’19, the shared task comprised two tracks: (1) a Shallow Track where the inputs were full UD structures with word order information removed and tokens lemmatised; and (2) a Deep Track where additionally, functional words and morphological information were removed. Moreover, each track had two subtracks: (a) restricted-resource, where only the data provided or approved as part of a track could be used for training models, and (b) open-resource, where any data could be used. The Shallow Track was offered in 11 languages, whereas the Deep Track in 3 ones. Systems were evaluated using both automatic metrics and direct assessment by human evaluators in terms of Readability and Meaning Similarity to reference outputs. We present the evaluation results, along with descriptions of the SR’19 tracks, data and evaluation methods, as well as brief summaries of the participating systems. For full descriptions of the participating systems, please see the separate system reports elsewhere in this volume.
%U https://aclanthology.org/2020.msr-1.1
%P 1-20

Markdown (Informal)

[The Third Multilingual Surface Realisation Shared Task (SR’20): Overview and Evaluation Results](https://aclanthology.org/2020.msr-1.1) (Mille et al., MSR 2020)

• The Third Multilingual Surface Realisation Shared Task (SR’20): Overview and Evaluation Results (Mille et al., MSR 2020)

ACL

• Simon Mille, Anya Belz, Bernd Bohnet, Thiago Castro Ferreira, Yvette Graham, and Leo Wanner. 2020. The Third Multilingual Surface Realisation Shared Task (SR’20): Overview and Evaluation Results. In Proceedings of the Third Workshop on Multilingual Surface Realisation, pages 1–20, Barcelona, Spain (Online). Association for Computational Linguistics.