中文实体关系抽取，pytorch，bilstm+attention

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）。

Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs

基于知识库的中文问答系统（biLSTM）

Source codes and corpora of paper "Iterated Dilated Convolutions for Chinese Word Segmentation"

reference tensorflow code for named entity tagging

Chinese & English Cws Pos Ner Entity Recognition implement using CNN bi-directional lstm and crf model with char embedding.基于字向量的CNN池化双向BiLSTM与CRF模型的网络，可能一体化的完成中文和英文分词，词性标注，实体识别。主要包括原始文本数据，数据转换,训练脚本,预训练模型,可用于序列标注研究.注意：唯一需要实现的逻辑是将用户数据转化为序列模型。分词准确率约为93%，词性标注准确率约为90%，实体标注（在本样本上）约为85%。

biLSTM/CNN based deep learning framework for Question Answer Selection.

Compare six baseline deep learning models on TrecQA

CNN+BiLSTM 기반 한국어 개체명 인식기입니다

A PyTorch implementation of the BI-LSTM-CRF model.

albert lstm crf实体识别，pytorch

State of the art Chinese Word Segmentation with Bi-LSTMs

💻 英文命名实体识别(NER)的研究

这里整理了本人在学习NLP过程中做的一些小项目

BiLSTM Model for Metaphor Detection

pytorch implementation of various models for snli and mnli task

a high performance tensorflow version for relation extraction of named entity

Bi-Directional Attention Flow for Machine Comprehensions

Named Entity Recognition

BiLSTM+CRF

Sequence Labeling implemented by BiLSTM using Tensorflow

Named entity recognition using deep learning

A transition-based dependency parser for both projective and non-projective trees, using Bi-LSTM as a feature extractor

Joint text classification on multiple levels with multiple labels, using a multi-head attention mechanism to wire two prediction tasks together.

Bangla news classification and generation

Ask Me: Question Generating Agent

命名实体识别-NER

命名实体识别平台

Hate speech detection from code-mixed Hindi-English tweets using deep learning models. This project reports an increment to the state-of-the-art in hate speech detection for English-Hindi code-mixed tweets. The models result in an improvement of about 12% in F-score over a past work that used statistical classifiers.