What Matters When Building Universal Multilingual Named Entity Recognition Models?

This project is a research paper implementation focused on ablation studies for NER. While scientifically valuable for understanding model design, it lacks a software moat, user base (0 stars), or unique dataset that would prevent replication. Frontier models (GPT-4, Gemini) have largely commoditized multilingual NER via zero-shot prompting, making specialized small-model architectures a niche optimization rather than a defensible product category.