Named Entity Recognition is widely used in NLP, but complex texts can present challenges. What are some creative ways you’ve improved the performance of NER models in tricky datasets like legal or medical text?
Named Entity Recognition is widely used in NLP, but complex texts can present challenges. What are some creative ways you’ve improved the performance of NER models in tricky datasets like legal or medical text?