The Third Multilingual Surface Realisation Shared Task (SR?20): Overview and Evaluation Results
Citation:
Anya Belz, Bernd Bohnet, Thiago Castro Ferreira, Yvette Graham, Simon Mille, Leo Wanner, The Third Multilingual Surface Realisation Shared Task (SR?20): Overview and Evaluation Results, Proceedings of the Third Multilingual Surface Realisation Workshop, Third Multilingual Surface Realisation Workshop, Virtual, 2020, 1 - 20Download Item:
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.
Sponsor
Grant Number
SFI stipend
13/RC/2106
Author's Homepage:
http://people.tcd.ie/ygrahamDescription:
PUBLISHEDVirtual
Author: Graham, Yvette
Sponsor:
SFI stipendOther Titles:
Proceedings of the Third Multilingual Surface Realisation WorkshopThird Multilingual Surface Realisation Workshop
Type of material:
Conference PaperCollections
Availability:
Full text availableSubject (TCD):
Digital Engagement , Natural Language Processing , natural language generationMetadata
Show full item recordLicences: