BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks

Understand

Biomedical Named Entity Recognition (NER) is a challenging problem in biomedical information processing due to the widespread ambiguity of out of context terms and extensive lexical variations.

• Performance on bioNER benchmarks continues to improve due to advances like BERT, GPT, and XLNet.
• FLAIR (1) is an alternative embedding model which is less computationally intensive than the others mentioned.
• We test FLAIR and its pretrained PubMed embeddings (which we term BioFLAIR) on a variety of bio NER tasks and compare those with results from BERT-type networks.