LivingNER: Named entity recognition

Given a plain text clinical case report document collection, participants must return the exact character offsets of all species mentions, both human and non-human.

Publication
Antonio Miranda-Escalada, Eulàlia Farré-Maduell, Salvador Lima-López, Darryl Estrada, Luis Gascó, Martin Krallinger (2022) Mention detection, normalization & classification of species, pathogens, humans and food in clinical documents: Overview of the LivingNER shared task and resources. Procesamiento del Lenguaje Natural, Revista nº 69, septiembre de 2022, pp. 241-253.
Competition
LivingNER: Named-Entity Recognition and entity linking for living being mentions
Language
Spanish
NLP topic
(named) entity recognition
Abstract task
Sequence labeling
Dataset
LivingNER
Year
2022
Publication link
http://journal.sepln.org/sepl…
Ranking metric
Micro F

Task results

System MicroPrecision MicroRecall MicroF1
Vicomtech NLP 0.9583 0.9438 0.9510
racai 0.9569 0.9439 0.9503
READ-Biomed 0.9540 0.9411 0.9475
SINAI 0.9571 0.9346 0.9457
plncmm 0.9455 0.9373 0.9414

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.