This repository provides a complete NER (Named Entity Recognition) solution using Google BERT for feature extraction fine-tuned with a Bidirectional LSTM CRF layer. The project supports both Chinese and English NER tasks, includes training pipelines with configurable parameters, and exposes a Flask-based HTTP service for serving NER predictions. The architecture leverages BERT’s contextual representations combined with sequence labeling through CRF decoding.