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

ABSTRACT: 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 dataset NEREL by introducing domain-specific entity
types. NEREL-BIO annotation scheme covers both general and biomedical domains
making it suitable for domain transfer experiments. NEREL-BIO provides
annotation for nested named entities as an extension of the scheme employed for
NEREL. Nested named entities may cross entity boundaries to connect to shorter
entities nested within longer entities, making them harder to detect.
  NEREL-BIO contains annotations for 700+ Russian and 100+ English abstracts.
All English PubMed annotations have corresponding Russian counterparts. Thus,
NEREL-BIO comprises the following specific features: annotation of nested named
entities, it can be used as a benchmark for cross-domain (NEREL -> NEREL-BIO)
and cross-language (English -> Russian) transfer. We experiment with both
transformer-based sequence models and machine reading comprehension (MRC)
models and report their results.
  The dataset is freely available at https://github.com/nerel-ds/NEREL-BIO.
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 dataset NEREL by introducing domain-specific entity
types. NEREL-BIO annotation scheme covers both general and biomedical domains
making it suitable for domain transfer experiments. NEREL-BIO provides
annotation for nested named entities as an extension of the scheme employed for
NEREL. Nested named entities may cross entity boundaries to connect to shorter
entities nested within longer entities, making them harder to detect.
  NEREL-BIO contains annotations for 700+ Russian and 100+ English abstracts.
All English PubMed annotations have corresponding Russian counterparts. Thus,
NEREL-BIO comprises the following specific features: annotation of nested named
entities, it can be used as a benchmark for cross-domain (NEREL -> NEREL-BIO)
and cross-language (English -> Russian) transfer. We experiment with both
transformer-based sequence models and machine reading comprehension (MRC)
models and report their results.
  The dataset is freely available at https://github.com/nerel-ds/NEREL-BIO.
NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities
http://arxiv.org/abs/2210.11913v1