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Large Language Model Assertion Pipeline (updated - 2/25/24)

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This code is for the large language model assertion pipeline. Detailed instructions coming soon!

Pipeline flow:

1. Run run_umls_synonym_ner.py and run_dataset_ner.py to build NER datasets (recommend using targeted NER prompts instead of broad NER prompts for NER dataset pull)
2. (Optional - highly recommended) Run run_ner_cosine_similarity.py followed by run_llm_filter_cosine_sim_ner_output.py to filter NER outputs (filter NER outputs to remove the low-yield named entities --> also helpful to review filtered NER outputs and remove those that are not related to your target entity)
3. Run run_extraction.py to build target-matcher and extract high-yield text from clinical notes
4. Run run_llm_assertion.py to generate LLM assertions