CodeNER: Code Prompting for Named Entity Recognition
📰 ArXiv cs.AI
CodeNER uses code prompting for named entity recognition, leveraging large language models to improve accuracy
Action Steps
- Leverage large language models like ChatGPT for named entity recognition
- Use code prompting to generate candidate named entity spans
- Capture external knowledge and context information to improve NER accuracy
- Integrate CodeNER into NLP pipelines for real-world applications
Who Needs to Know This
NLP researchers and AI engineers can benefit from CodeNER as it enhances named entity recognition capabilities, while software engineers can integrate this approach into their NLP pipelines
Key Insight
💡 Code prompting can improve named entity recognition accuracy by capturing external knowledge and context information
Share This
🤖 CodeNER: Enhancing named entity recognition with code prompting and large language models!
DeepCamp AI