Evidence map›Paper›PMID 37004189›Full record

ArticleBioinformatics (Oxford, England)2023

NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities.

Natalia Loukachevitch, Suresh Manandhar, Elina Baral, Igor Rozhkov, Pavel Braslavski, Vladimir Ivanov, Tatiana Batura, Elena Tutubalina

Abstract readDataset
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Natalia LoukachevitchLomonosov Moscow State University, Moscow 19899, Russia.
Suresh ManandharMadan Bhandari University of Science and Technology, Chitlang 44600, Nepal.
Elina BaralMadan Bhandari University of Science and Technology, Chitlang 44600, Nepal.
Igor RozhkovLomonosov Moscow State University, Moscow 19899, Russia.
Pavel BraslavskiUral Federal University, Yekaterinburg 620002, Russia.
Vladimir IvanovInnopolis University, Innopolis 420500, Russia.
Tatiana BaturaA.P. Ershov Institute of Informatics Systems, Novosibirsk 630090, Russia.ORCID 0000-0003-4333-7888
Elena TutubalinaHSE University, Moscow 101000, Russia.ORCID 0000-0001-7936-0284

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThis article 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.

resultsNEREL-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 models and report their results. AVAILABILITY AND IMPLEMENTATION: The dataset and annotation guidelines are freely available at https://github.com/nerel-ds/NEREL-BIO.

Indexed as

Natural Language ProcessingSemanticsLanguagePubMed

Identifiers

PMID37004189
PMCPMC10129873

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.