activity
20172022
most citedNEREL: A Russian Dataset with Nested Named Entities, Relations and Events

3 citations · 11 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CL2022

Taxonomy Enrichment with Text and Graph Vector Representations

Irina Nikishina, Mikhail Tikhomirov, Varvara Logacheva +3

Knowledge graphs such as DBpedia, Freebase or Wikidata always contain a taxonomic backbone that allows the arrangement and structuring of various concepts in accordance with the hy…

cs.CL20213 cited

NEREL: A Russian Dataset with Nested Named Entities, Relations and Events

Natalia Loukachevitch, Ekaterina Artemova, Tatiana Batura +6

In this paper, we present NEREL, a Russian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it co…

cs.CL2020

Studying Taxonomy Enrichment on Diachronic WordNet Versions

Irina Nikishina, Alexander Panchenko, Varvara Logacheva +1

Ontologies, taxonomies, and thesauri are used in many NLP tasks. However, most studies are focused on the creation of these lexical resources rather than the maintenance of the exi…

cs.CL2020

Improving Results on Russian Sentiment Datasets

Anton Golubev, Natalia Loukachevitch

In this study, we test standard neural network architectures (CNN, LSTM, BiLSTM) and recently appeared BERT architectures on previous Russian sentiment evaluation datasets. We comp…

cs.CL20201 cited

Attention-Based Neural Networks for Sentiment Attitude Extraction using Distant Supervision

Nicolay Rusnachenko, Natalia Loukachevitch

In the sentiment attitude extraction task, the aim is to identify <<attitudes>> -- sentiment relations between entities mentioned in text. In this paper, we provide a study on atte…

cs.CL20201 cited

Studying Attention Models in Sentiment Attitude Extraction Task

Nicolay Rusnachenko, Natalia Loukachevitch

In the sentiment attitude extraction task, the aim is to identify <<attitudes>> -- sentiment relations between entities mentioned in text. In this paper, we provide a study on atte…