kamalkraj/BERT-NER

BERT-NER is a legacy reference implementation from the 2018-2019 era of NLP. While it boasts a high star count (1,249) and substantial forks, these are historical metrics reflecting its past status as a pioneer implementation. In the current market, it has no defensibility. The core logic has been entirely commoditized by the Hugging Face Transformers library, which offers more robust, maintained, and optimized versions of the same code. Furthermore, NER as a task has shifted from specialized fine-tuning of small encoders (like BERT) to zero-shot or few-shot extraction via Large Language Models (LLMs) from frontier labs. The project's zero velocity confirms it is effectively an unmaintained archive. Any developer seeking this functionality would today use standard libraries like spaCy or Transformers, or simply query an LLM API, rendering this standalone implementation obsolete.