Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian

1 code implementation • 3 Jun 2022 • Tatiana Shamardina, Vladislav Mikhailov, Daniil Chernianskii, Alena Fenogenova, Marat Saidov, Anastasiya Valeeva, Tatiana Shavrina, Ivan Smurov, Elena Tutubalina, Ekaterina Artemova

The first task is framed as a binary classification problem.

Dialogue Evaluation Machine Translation +5

Russian News Clustering and Headline Selection Shared Task

1 code implementation • 3 May 2021 • Ilya Gusev, Ivan Smurov

The presented datasets for event detection and headline selection are the first public Russian datasets for their tasks.

Event Detection Headline generation

RuREBus: a Case Study of Joint Named Entity Recognition and Relation Extraction from e-Government Domain

no code implementations • 29 Oct 2020 • Vitaly Ivanin, Ekaterina Artemova, Tatiana Batura, Vladimir Ivanov, Veronika Sarkisyan, Elena Tutubalina, Ivan Smurov

We show-case an application of information extraction methods, such as named entity recognition (NER) and relation extraction (RE) to a novel corpus, consisting of documents, issued by a state agency.

named-entity-recognition NER +1

NoPropaganda at SemEval-2020 Task 11: A Borrowed Approach to Sequence Tagging and Text Classification

1 code implementation • SEMEVAL 2020 • Ilya Dimov, Vladislav Korzun, Ivan Smurov

This paper describes our contribution to SemEval-2020 Task 11: Detection Of Propaganda Techniques In News Articles.

Relation Extraction Text Classification

So What's the Plan? Mining Strategic Planning Documents

1 code implementation • 1 Jul 2020 • Ekaterina Artemova, Tatiana Batura, Anna Golenkovskaya, Vitaly Ivanin, Vladimir Ivanov, Veronika Sarkisyan, Ivan Smurov, Elena Tutubalina

In this paper we present a corpus of Russian strategic planning documents, RuREBus.

Machine Learning

Tagging and parsing of multidomain collections

1 code implementation • Proceedings of the International Conference “Dialogue 2020” 2020 • Alexey Sorokin, Ivan Smurov, Denis Kirianov

In this paper we describe our submission to GramEval2020 competition on morphological tagging, lemmatization and dependency parsing.

Dependency Parsing Language Modelling +2

AGRR 2019: Corpus for Gapping Resolution in Russian

no code implementations • 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.

AGRR-2019: A Corpus for Gapping Resolution in Russian

no code implementations • 10 Jun 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.