基于python实现深度学习bi-lstm-crf的（分词-词性标注-实体识别）实现

# SegPosNer_Bilstm_CRF 基于深度学习bi_lstm_crf的(分词/词性标注/实体识别)实现. # Data Demo seg:train.txt ``` 预 B 约 E 即 B 可 E 获 B 得 E 考 B 试 E 大 S 礼 B 包 E ``` pos:pos_train.txt ``` 迈向 v 充满 v 希望 n 的 u 新 a 世纪 n ``` # Run > python train.py ``` start to training... step: 20/20000... loss: 60.6413... 1.0220 sec/batch step: 40/20000... loss: 55.0804... 1.1040 sec/batch . . step: 3760/20000... loss: 2.1385... 0.9900 sec/batch step: 3780/20000... loss: 1.9285... 0.9870 sec/batch step: 3800/20000... loss: 1.5843... 1.0100 sec/batch val len: 5000 accuracy:85.58%. best:87.26% ``` # Test > python test.py ``` start to testing... word / tag / pre 上 / B / B 述 / E / E 担 / B / B 保 / E / E 不 / S / B 构 / B / E 成 / E / S 关 / B / B 联 / E / B 交 / B / E 易 / E / S 。 / S / S ``` # References https://github.com/Franck-Dernoncourt/NeuroNER https://github.com/rockyzhengwu/FoolNLTK