LINGUIST List 32.1537

Mon May 03 2021

Confs: Comp Ling/Online

Editor for this issue: Lauren Perkins <>

Date: 03-May-2021
From: Martin Krallinger <>
Subject: Medical Documents Profession Recognition shared task at IberLEF/SEPLN2021
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Medical Documents Profession Recognition shared task at IberLEF/SEPLN2021
Short Title: MEDDOPROF

Date: 22-Sep-2021 - 22-Sep-2021
Location: Virtual, Spain
Contact: Martin Krallinger
Contact Email: < click here to access email >
Meeting URL:

Linguistic Field(s): Computational Linguistics

Meeting Description:

We are organizing the first shared task focusing on automatic recognition of professions and occupational status (and normalization to standard multilingual terminologies) in medical documents.

The relevance of text mining of professions and occupational status encompasses multiple human-interest areas, from health and social services, competitive intelligence, human resources, legal NLP and even gender studies.

The need to implement advanced NER systems to detect professions in medical texts has been underscored by the current pandemic, in which the risk of selected occupational groups has resulted in higher mortality and morbidity for these segments of the population. The relationships between disorders and professions may be explained by different factors like increased contact/exposure to hazardous substances, allergens or pathogens; physical injuries due to occupational accidents; higher degrees of social interaction of some professions, or even work-related conditions affecting mental health, just to name a few.
Additionally, targeted vaccination plans also benefit from better characterization of patient professions.

Following the success of previously organized shared tasks (i.e. Cantemist, PharmaCoNER, or Meddocan), we are now launching the MEDDOPROF shared task as part of the IberLEF 2021 evaluation initiative (co-located with SEPLN 2021), with the following sub-tracks:

MEDDOPROF-NER: automatic detection of mentions of occupations (profession, employment status and activities).
MEDDOPROF-CLASS: finding mentions of occupations and classifying them, whether they refer to the patients themselves, their family members or healthcare professionals.
MEDDOPROF-NORM: mapping detected occupation mentions to their corresponding concept identifiers from standard multilingual occupation terminologies (ESCO and SNOMED-CT).

Key information:
Annotation guidelines:
Google Group for updates:

Test set release (start of evaluation period): June 1, 2021
End of evaluation period (system submissions): June 7, 2021
Working papers submission: June 21, 2021
Notification of acceptance (peer-reviews): June 27, 2021
Camera-ready system descriptions: July 4, 2021
IberLEF SEPLN 2021: September 2021

Publications and IBERLEF/SEPLN2021 workshop
Teams participating in MEDDOPROF will be invited to contribute a systems description paper for the IberLEF (SEPLN 2021) Working Notes proceedings, and a short presentation of their approach at the IberLEF 2021 workshop.

Main Organizers:
Martin Krallinger, Barcelona Supercomputing Center, Spain
Eulàlia Farré, Barcelona Supercomputing Center, Spain
Salvador Lima, Barcelona Supercomputing Center, Spain
Vicent Briva-Iglesias, D-REAL, Dublin City University, Ireland
Antonio Miranda-Escalada, Barcelona Supercomputing Center, Spain

Page Updated: 03-May-2021