This repository implements a Lattice LSTM model for Chinese NER, combining character-level LSTM with word (lattice) embeddings as input. The model uses bidirectional LSTM layers followed by a CRF layer for sequence labeling, taking advantage of both character sequences and pre-defined word boundaries in Chinese text. It supports pretrained character and word embeddings for improved performance.