Assessing multiple word embeddings for named entity recognition of professions and occupations in health-related social media

This paper presents our contribution to the ProfNER shared task. Our work focused on evaluating different pre-trained word embedding representations suitable for the task. We further explored combinations of embeddings in order to improve the overall results.