This is an experimental Tensorflow implementation of Lattice LSTM - Chinese NER Using Lattice LSTM. For details about Lattice LSTM please refer to the paper Chinese NER Using Lattice LSTM by Yue Zhang and Jie Yang.
Python: 3.5
TensorFlow: 1.5
CoNLL format (prefer BIOES tag scheme), with each character its label for one line. Sentences are splited with a null line.
美 B-LOC
国 E-LOC
的 O
华 B-PER
莱 I-PER
士 E-PER
我 O
跟 O
他 O
谈 O
笑 O
风 O
生 O
The pretrained character and word embeddings are the same with the embeddings in the baseline of RichWordSegmentor
Character embeddings: gigaword_chn.all.a2b.uni.ite50.vec
Word(Lattice) embeddings: ctb.50d.vec
Crawled from the Sina Finance, it includes the resumes of senior executives from listed companies in the Chinese stock market. Details can be found in our paper.