# AGRR-2019: A Corpus for Gapping Resolution in Russian

arXiv: https://arxiv.org/abs/1906.04099 · HTML: https://mlsanity.com/paper/1906.04099/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jun 2019.

## Built on by (most cited first, 1 of 1)

- [RuSentEval: Linguistic Source, Encoder Force!](https://mlsanity.com/paper/2103.00573/) (2021)

## Abstract (arXiv)

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.