(Read the full entry here)

The general objective of the shared task is to produce a well-formed sentence out of the given input structure. As in SR’18 and SR'11, the proposed shared task comprises two tracks with different levels of complexity:

• Shallow Track (Track 1): This track starts from genuine UD structures from which word order information has been removed and the tokens have been lemmatized, i.e., from unordered dependency trees with lemmatized nodes that hold PoS tags and morphological information as found in the original annotations. The task consists in determining the word order and inflecting the words.
• Deep Track (Track 2): This track starts from UD structures from which functional words (in particular, auxiliaries, functional prepositions and conjunctions) and surface-oriented morphological information have been removed. In addition to what has to be done for the Shallow Track, the Deep Track thus consists in introducing the removed functional words and morphological features.

Training and development data: Please register for the task to receive a link and download freely the data. The compressed folder contains (i) the original UD datasets for 11 languages as they can be found on the UD page (20 + 20 files); (ii) the Track 1 datasets (20 + 20 files); (iii) the Track 2 datasets (9 + 9 files); (iv) statistics about all the datasets (98 files).

Paper about dataset (INLG 2018): Download
More informal documentation: Open

The results of the Surface Realization Shared Task 2019 will be presented during the Multilingual Surface Realization Workshop @EMNLP 2019. In 2018, the first edition of the workshop took place in Melbourne, Australia, in collocation with ACL'18. Eight teams participated to the shared task and to the workshop. The proceedings of the workshop with the system descriptions and the task overview and results can be found here.

The shared task is organized by the Multilingual Surface Realization workshop committee: Anja Belz, Bernd Bohnet, Yvette Graham, Simon Mille and Leo Wanner.

If you have any question or comment (after reading the full details available at

http://taln.upf.edu/pages/msr2019-ws/SRST.html )

please write to: [email protected]