Intent Detection and Entity Extraction from Biomedical Literature
Ankan Mullick, Mukur Gupta, Pawan Goyal · 2024
Biomedical queries have become increasingly prevalent in web searches, reflecting the growing interest in accessing biomedical literature.Despite recent research on large-language models (LLMs) motivated by endeavors to attain generalized intelligence, their efficacy in replacing task and domain-specific natural language understanding approaches remains questionable.In this paper, we address this question by conducting a comprehensive empirical evaluation of intent detection and named entity recognition (NER) tasks from biomedical text.We show that Supervised Fine Tuned approaches are still relevant and more effective than general-purpose LLMs.Biomedical transformer models such as PubMedBERT can surpass ChatGPT on NER task with only 5 supervised examples.