Named Entity Recognition (NER) Comparison

[Cgarg9]

Description:

To help users understand the differences in Named Entity Recognition (NER) models, add a notebook that applies multiple NER techniques on the same dataset and compares results.

Tasks:

• Create a notebook to compare Spacy, NLTK, Stanford NER, and transformer-based models (e.g., BERT, RoBERTa, GPT-4 for NER).
• Provide visual comparisons and discuss precision, recall, and real-world use cases.
• Summarize key takeaways for each method.
• Name the notebook ner_comparison.ipynb.
• Update the README file with relevant references.