sequence-labeling

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

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

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.

CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition

Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)

Empower Sequence Labeling with Task-Aware Language Model

The BiLSTM-CRF model implementation in Tensorflow, for sequence labeling tasks.

word2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, information retrieval, information extraction (i.e., entity, relation and event extraction), knowledge graph, text generation, network embedding

A TensorFlow implementation of Recurrent Neural Networks for Sequence Classification and Sequence Labeling

Learning Named Entity Tagger from Domain-Specific Dictionary

This is the template code to use BERT for sequence lableing and text classification, in order to facilitate BERT for more tasks. Currently, the template code has included conll-2003 named entity identification, Snips Slot Filling and Intent Prediction.

LSTM-CRF in PyTorch

AdaSeq: An All-in-One Library for Developing State-of-the-Art Sequence Understanding Models

Deep neural models for core NLP tasks (Pytorch version)

A Japanese tokenizer based on recurrent neural networks

a Deep Learning Framework for Text https://delft.readthedocs.io/