Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

Named Entity Recognition (LSTM + CRF) - Tensorflow

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

A machine learning software for extracting information from scholarly documents

🇺🇸 a python library for parsing unstructured address strings into address components

中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）

Empower Sequence Labeling with Task-Aware Language Model

🔖 A toolkit for making domain-specific probabilistic parsers

A python binding for crfsuite

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

An easy-to-use named entity recognition (NER) toolkit, implemented the Bi-LSTM+CRF model in tensorflow.

序列化标注工具，基于PyTorch实现BLSTM-CNN-CRF模型，CoNLL 2003 English NER测试集F1值为91.10%（word and char feature）。

LSTM-CRF in PyTorch

ACL 2018: Hybrid semi-Markov CRF for Neural Sequence Labeling (http://aclweb.org/anthology/P18-2038)

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s multilingual dataset, MIT corpus, E-commerce Shopping Assistant (ECSA) dataset, CoNLL2003 NER, ELMo, BERT, XLNet

LSTM+CRF NER

Easy to use NLP library built on PyTorch and TorchText

Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling

End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF implement in pyotrch

自然语言处理工具Macropodus，基于Albert+BiLSTM+CRF深度学习网络架构，中文分词，词性标注，命名实体识别，新词发现，关键词，文本摘要，文本相似度，科学计算器，中文数字阿拉伯数字(罗马数字)转换，中文繁简转换，拼音转换。tookit(tool) of NLP，CWS(chinese word segnment)，POS(Part-Of-Speech Tagging)，NER(name entity recognition)，Find(new words discovery)，Keyword(keyword extraction)，Summarize(text summarization)，Sim(text similarity)，Calculate(scientific calculator)，Chi2num(chinese number to arabic number)

KoBERT와 CRF로 만든 한국어 개체명인식기 (BERT+CRF based Named Entity Recognition model for Korean)

NLP for human. A fast and easy-to-use natural language processing (NLP) toolkit, satisfying your imagination about NLP.

An implementation of Conditional Random Fields (CRFs) with Deep Learning Method

A frame-semantic parsing system based on a softmax-margin SegRNN.

面向中文电子病历的命名实体识别

g2pC: A Context-aware Grapheme-to-Phoneme Conversion module for Chinese

Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing