FreedomIntelligence/Evaluation-of-ChatGPT-on-Information-Extraction
An Evaluation of ChatGPT on Information Extraction task, including Named Entity Recognition (NER), Relation Extraction (RE), Event Extraction (EE) and Aspect-based Sentiment Analysis (ABSA).
This project helps researchers and developers understand the capabilities and limitations of large language models like ChatGPT for information extraction tasks. It takes raw text or pre-processed datasets and outputs detailed performance metrics, error analyses, and robustness insights across various extraction types. The primary users are researchers in natural language processing or AI developers evaluating LLMs for production applications.
134 stars. No commits in the last 6 months.
Use this if you are a researcher or developer who needs to thoroughly evaluate how well ChatGPT performs on tasks like identifying entities, relationships, events, or sentiment from text.
Not ideal if you are looking for a pre-built solution to directly perform information extraction on your own data without extensive setup or analysis.
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134
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Python
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Last pushed
Jan 17, 2024
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