AGRR 2019: Corpus for Gapping Resolution in Russian

WS 2019  ·  Maria Ponomareva, Kira Droganova, Ivan Smurov, Tatiana Shavrina ·

This paper provides a comprehensive overview of the gapping dataset for Russian that consists of 7.5k sentences with gapping (as well as 15k relevant negative sentences) and comprises data from various genres: news, fiction, social media and technical texts. The dataset was prepared for the Automatic Gapping Resolution Shared Task for Russian (AGRR-2019) - a competition aimed at stimulating the development of NLP tools and methods for processing of ellipsis. In this paper, we pay special attention to the gapping resolution methods that were introduced within the shared task as well as an alternative test set that illustrates that our corpus is a diverse and representative subset of Russian language gapping sufficient for effective utilization of machine learning techniques.

PDF Abstract

Code
Add Remove Mark official

No code implementations yet. Submit your code now

Tasks
Add Remove

Datasets

  Add Datasets introduced or used in this paper

Results from the Paper
Add Remove

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods
Add Remove

No methods listed for this paper. Add relevant methods here
Contact us on: hello@paperswithcode.com . Papers With Code is a free resource with all data licensed under CC-BY-SA.
Terms Data policy Cookies policy