/cross-lingual-parsing

Primary LanguagePython

Multi-source synthetic treebank creation for improved cross-lingual dependency parsing

This is an open source implementation of our approach to creating synthetic treebanks for cross-lingual dependency parsing. It includes a combination of:

  • machine translation
  • annotation projection
  • maximum spanning tree algorithm

Francis Tyers, Mariya Sheyanova, Aleksandra Martynova, Pavel Stepachev and Konstantin Vinogorodskiy. Multi-source synthetic treebank creation for improved cross-lingual dependency parsing In Proceedings of the Second Workshop on Universal Dependencies (UDW 2018) EMNLP18

A part of software created during our research is reused in a feature UD Annotatrix. The feature aims to make treebanks annotation easier by automatically annotating the sentences.

At the moment, we have a custom extantion of UD Annotatrix with this feature.

In future, it will be merged to the main repository.

FAQ

Q: How to use feature UD Annotatrix?

A: Please, read our guide.

Q: How to deploy?

A: Please, read our deploy guide.

Q: Where can I find all useful information about UD Annotatrix tool?

A: Please, check the main repository.

Publication

If you use this software for academic research, please cite the paper in question:

@InProceedings{W18-6017,
  author = 	"Tyers, Francis
		and Sheyanova, Mariya
		and Martynova, Aleksandra
		and Stepachev, Pavel
		and Vinogorodskiy, Konstantin",
  title = 	"Multi-source synthetic treebank creation for improved cross-lingual dependency parsing",
  booktitle = 	"Proceedings of the Second Workshop on Universal Dependencies (UDW 2018)",
  year = 	"2018",
  publisher = 	"Association for Computational Linguistics",
  pages = 	"144--150",
  location = 	"Brussels, Belgium",
  url = 	"http://aclweb.org/anthology/W18-6017"
}

Team and Mentors

Mentors

  • Olga Lyashevskaya
  • Francis Tyers

Team

Acknowledgements

The article was prepared within the framework of the Academic Fund Programme at the National Research University Higher School of Economics (HSE) in 2016 — 2018 (grant No17-05-0043) and by the Russian Academic Excellence Project «5-100».