LLM Prompt Engineering & Response Evaluation Project
OtherTextEntity Ner ClassificationSegmentation
Conducted structured prompt engineering and response evaluation tasks across multiple large language models. Designed prompts to test reasoning, factual consistency, summarization accuracy, and instruction-following capabilities.
Performed response grading using defined quality criteria including clarity, coherence, bias detection, hallucination identification, and logical soundness.
Organized evaluation results in spreadsheets to track consistency and performance trends. Applied domain-specific knowledge in Animal Science to validate AI outputs in agricultural contexts. Maintained structured workflow processes to ensure repeatable and high-accuracy results.
Conducted structured prompt engineering and response evaluation tasks across multiple large language models. Designed prompts to test reasoning, factual consistency, summarization accuracy, and instruction-following capabilities. Performed response grading using defined quality criteria including clarity, coherence, bias detection, hallucination identification, and logical soundness. Organized evaluation results in spreadsheets to track consistency and performance trends. Applied domain-specific knowledge in Animal Science to validate AI outputs in agricultural contexts. Maintained structured workflow processes to ensure repeatable and high-accuracy results.
2023