307 Open source projects that are alternatives of or similar to Macropodus

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.

keras+bi-lstm+crf，中文命名实体识别

Keras solution of Chinese NER task using BiLSTM-CRF/BiGRU-CRF/IDCNN-CRF model with Pretrained Language Model: supporting BERT/RoBERTa/ALBERT

Named Entity Recognition (LSTM + CRF) - Tensorflow

Empower Sequence Labeling with Task-Aware Language Model

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

datagrand 2019 information extraction competition rank9

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.

搜索所有中文NLP数据集，附常用英文NLP数据集

reference tensorflow code for named entity tagging

中文自然语言的实体抽取和意图识别（Natural Language Understanding），可选Bi-LSTM + CRF 或者 IDCNN + CRF

No description or website provided.

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

命名体识别(NER)综述-论文-模型-代码(BiLSTM-CRF/BERT-CRF)-竞赛资源总结-随时更新

This repo contains a PyTorch implementation of a BiLSTM-CRF model for named entity recognition task.

An Inplementation of CRF (Conditional Random Fields) in PyTorch 1.0

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

A Dataset of German Legal Documents for Named Entity Recognition

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

LSTM-CRF for NER with ConLL-2002 dataset

reference pytorch code for named entity tagging

keras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS

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%。

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

中文NER的那些事儿

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

pytorch实现bert做seq2seq任务，使用unilm方案,现在也可以做自动摘要，文本分类，情感分析，NER，词性标注等任务,支持GPT2进行文章续写。

面向中文电子病历的命名实体识别

KU_NERDY 이동엽, 임희석 (2017 국어 정보 처리 시스템경진대회 금상) - 한글 및 한국어 정보처리 학술대회

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

Text summarization starting from scratch.

GROBID extension for identifying and normalizing physical quantities.

基于vue3 element plus的快速表单生成器

基于BERT的中文命名实体识别

KgCLUE: 大规模中文开源知识图谱问答

一套针对中文实体识别的BLSTM-CRF解决方案

A small NLP SAAS project that summarize a webpage

No description or website provided.

implemented some computer vision problems

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

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.

TextRank implementation for C#

Named Entity Recognition for biomedical entities

C++ based implementation of StatNLP framework

9 tools for Goodreads.com, for finding people based on the books they’ve read, finding books popular among the people you follow, following new book reviews, etc

Pure Rust port of CRFsuite: a fast implementation of Conditional Random Fields (CRFs)

NER, syntax markup visualizations

chatbot_ner: Named Entity Recognition for chatbots.

从模型训练到部署，实战知识图谱(Knowledge Graph)&自然语言处理(NLP)。涉及 Tensorflow, Bert+Bi-LSTM+CRF,Neo4j等 涵盖 Named Entity Recognition,Text Classify,Information Extraction,Relation Extraction 等任务。

NER（命名实体识别）中文语料，一站式获取

Pytorch Implementation of "Adaptive Co-attention Network for Named Entity Recognition in Tweets" (AAAI 2018)

A simple zero-dependency React component for tagging user-defined entities within a block of text.

Named-entity recognition for Ruby

使用预训练语言模型ALBERT做中文NER

a Deep Learning Framework for Text

using bilstm-crf,bert and other methods to do sequence tagging task

推荐算法、相似度算法、布隆过滤器、均值算法、一致性Hash、数据结构、leetcode练习

PyTorch implementation of the paper: Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding. Su Zhu, Ruisheng Cao, Lu Chen and Kai Yu.

Malware similarity platform with modularity in mind.

a Fairseq fork for sequence tagging/labeling tasks