IAI @ S ocial D is NER : Catch me if you can! Capturing complex disease mentions in tweets (2022)

Abstract: Biomedical NER is an active research area today. Despite the availability of state-of-the-art models for standard NER tasks, their performance degrades on biomedical data due to OOV entities and the challenges encountered in specialized domains. We use Flair-NER framework to investigate the effectiveness of various contextual and static embeddings for NER on Spanish tweets, in particular, to capture complex disease mentions.

## motivation in this paper, we present our system which recognizes disease mentions in spanish tweets as part of the socialdisner challenge @xcite . the motivation of our work is to: ## results ## conclusion in this paper, we studied the existing problems for bio-medical ner on twitter data and further shown the effectiveness of contextualized embeddings. in addition, we observed a potential in these systems to improve the quality of gold annotations. regardless of the high performance of the presented systems, post-processing remains a key step to achieve high quality extractions of target entities. in future work, we would like to investigate more effective post-processing strategies and a finer tagging schema such as nested annotations for a more accurate detection of complex disease mentions.