TigreGotico/simple_NER

Simple_NER is a legacy project (7+ years old) that implements basic dictionary and regex-based entity extraction. With only 41 stars and zero recent activity, it lacks any significant moat or community traction. In the current NLP landscape, rule-based systems are relegated to specific high-precision/low-compute niches (like PII masking or strictly defined financial entity extraction), and even then, frameworks like spaCy (via EntityRuler) or GLiNER provide significantly more robust and maintainable alternatives. Frontier labs and cloud providers (AWS Comprehend, Google Natural Language API) have effectively commoditized this capability, and modern LLMs can perform zero-shot NER with far higher accuracy than a static rule-based system. The project serves more as a historical reference or a simple tutorial than a viable production-grade tool in the current era of transformer-based NLP.