activity
20202022
most citedNEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities

22 citations · 28 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2022★ 22 cited

NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities

Natalia Loukachevitch, Suresh Manandhar, Elina Baral +5

This paper describes NEREL-BIO -- an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain da…

cs.CL2022★ 2 cited

RuNNE-2022 Shared Task: Recognizing Nested Named Entities

Ekaterina Artemova, Maxim Zmeev, Natalia Loukachevitch +4

The RuNNE Shared Task approaches the problem of nested named entity recognition. The annotation schema is designed in such a way, that an entity may partially overlap or even be ne…

cs.CL2021★ 3 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★ 1 cited

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

Vitaly Ivanin, Ekaterina Artemova, Tatiana Batura +4

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, issue…

cs.CL2020

So What's the Plan? Mining Strategic Planning Documents

Ekaterina Artemova, Tatiana Batura, Anna Golenkovskaya +5

In this paper we present a corpus of Russian strategic planning documents, RuREBus. This project is grounded both from language technology and e-government perspectives. Not only n…