ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish

Rosa Montañés-Salas, Irene López-Bosque, Luis García-Garcés, Rafael del-Hoyo-Alonso


Abstract
ITAINNOVA participates in SocialDisNER with a hybrid system which combines Transformer-based Language Models (LMs) with a custom-built gazetteer for Approximate String Matching (ASM) and dedicated text processing techniques for the social media domain. Additionally, zero-shot classification capabilities have been explored in order to support different parts of the system. An extensive analysis on the interactions of these components has been accomplished, making the system stand out above the mean performance of all the participating teams.
Anthology ID:
2022.smm4h-1.21
Volume:
Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Editors:
Graciela Gonzalez-Hernandez, Davy Weissenbacher
Venue:
SMM4H
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
71–74
Language:
URL:
https://aclanthology.org/2022.smm4h-1.21
DOI:
Bibkey:
Cite (ACL):
Rosa Montañés-Salas, Irene López-Bosque, Luis García-Garcés, and Rafael del-Hoyo-Alonso. 2022. ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 71–74, Gyeongju, Republic of Korea. Association for Computational Linguistics.
Cite (Informal):
ITAINNOVA at SocialDisNER: A Transformers cocktail for disease identification in social media in Spanish (Montañés-Salas et al., SMM4H 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.smm4h-1.21.pdf