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Description | Mitigation | Responsible Party |
Failure to identify business questions, or picking too many or too few | Draft appropriate business questions | Lee Harland, John Wise, Bruce Press |
Meeting on Jan 17, 2024: recording (password: w*Qi2#D9) and transcript BioCypher could be the right KG. It contains Open Targets. Required steps are:
| The Hyve | |
Technology research, feature and cost analysis, and selection | Jon Stevens, Etzard Stolte, Helena Deus; Brian Evarts; Wouter Franke, Matthijs van der Zee | |
Perhaps The Hyve team has a ready answer | ||
Failure to download a large volume of data (all of the PubMed as a maximum) for the prompt-tuning of the LLM | TBD | |
Failure to perform KG generation from text by an LLM |
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Failure to perform local KG comparison with calculation of a score |
| |
Failure to generate a proper query for a KG database system by an LLM | Technology research. Code generation by LLMs is a common task, so this risk may be seen as low. See refs 7, 8 below | |
Failure to build a prototypical target discovery pipeline on the limited budget in case of mounting technical difficulties | Schedule the project in phases. Aim to answer known unknowns and to establish risk mitigation strategies early in this phase (“project elaboration”) |
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References
https://www.sciencedirect.com/science/article/pii/S1359644613001542
Open LLM Leaderboard: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
Chatbot Arena: https://chat.lmsys.org/?arena
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
Knowledge-Consistent Dialogue Generation with Language Models and Knowledge Graphs