308 Open source projects that are alternatives of or similar to Bert_ner

基于Pytorch和torchtext的知识图谱深度学习框架。

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

ChineseNER based on BERT, with BiLSTM+CRF layer

Papers and Book to look at when starting NLP 📚

Federated Knowledge Extraction Framework

DaNLP is a repository for Natural Language Processing resources for the Danish Language.

中文分词 词性标注 命名实体识别 依存句法分析 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁 自然语言处理

modest natural-language processing

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%。

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

基于深度学习的自然语言处理库

A pythonic wrapper for Stanford CoreNLP.

Inference with state-of-the-art models (pre-trained by LD-Net / AutoNER / VanillaNER / ...)

A TensorFlow implementation of Neural Sequence Labeling model, which is able to tackle sequence labeling tasks such as POS Tagging, Chunking, NER, Punctuation Restoration and etc.

这是一款基于web的通用文本标注工具，支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注，同时也支持文本的迭代标注和实体的嵌套标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模，并设计了全新高效的标注方式，提升了用户体验和标注效率。此外，本工具增加了审核环节，可对多人的标注结果进行一致性检验和调整，提高了标注语料的准确率和可靠性。

Embedding, NMT, Text_Classification, Text_Generation, NER etc.

Lexicon-based Named Entity Recognition

reference tensorflow code for named entity tagging

The CRF Layer was implemented by using Chainer 2.0. Please see more details here: https://createmomo.github.io/2017/09/12/CRF_Layer_on_the_Top_of_BiLSTM_1/

Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

Transformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI

Named Entity Recognition data for Europeana Newspapers

Open Source REST API for named entity extraction, named entity linking, named entity disambiguation, recommendation & reconciliation of entities like persons, organizations and places for (semi)automatic semantic tagging & analysis of documents by linked data knowledge graph like SKOS thesaurus, RDF ontology, database(s) or list(s) of names

面向中文电子病历的命名实体识别

Chinese NER using Lattice LSTM. Code for ACL 2018 paper.

😋本项目旨在通过Tensorflow基于BiLSTM+CRF实现中文分词、词性标注、命名实体识别（NER）。

CrossWeigh: Training Named Entity Tagger from Imperfect Annotations

包含传统的基于统计模型(CRF)和基于深度学习(Embedding-Bi-LSTM-CRF)下的医疗数据命名实体识别

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

Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

👩‍🏫 Advanced NLP with spaCy: A free online course

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.

Macadam是一个以Tensorflow(Keras)和bert4keras为基础，专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。

CCKS2019评测任务五-公众公司公告信息抽取，第3名

Deep neural network based model for sequence to sequence classification

Implementation of Nested Named Entity Recognition using BERT

System for Medical Concept Extraction and Linking

bert-bilstm-crf implemented in pytorch for named entity recognition.

Chinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取

基于 TensorFlow & PaddlePaddle 的通用序列标注算法库（目前包含 BiLSTM+CRF, Stacked-BiLSTM+CRF 和 IDCNN+CRF，更多算法正在持续添加中）实现中文分词（Tokenizer / segmentation）、词性标注（Part Of Speech, POS）和命名实体识别（Named Entity Recognition, NER）等序列标注任务。

🏡 Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

data resource untuk NLP bahasa indonesia

瑞金医院MMC人工智能辅助构建知识图谱大赛-baseline

📖 Labeled examples from wiki dumps in Python

GERBIL - General Entity annotatoR Benchmark

TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition (ACL 2020)

Tensorflow-LSTM-CRF tool for Named Entity Recognizer

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

Dilated CNNs for NER in TensorFlow

A PyTorch implementation of GraphRel

NLP research：基于tensorflow的nlp深度学习项目，支持文本分类/句子匹配/序列标注/文本生成 四大任务

reference pytorch code for named entity tagging

Python/Django based webapps and web user interfaces for search, structure (meta data management like thesaurus, ontologies, annotations and named entities) and data import (ETL like text extraction, OCR and crawling filesystems or websites)

Language model finetuning on NER with an easy interface, and cross-domain evaluation. We released NER models finetuned on various domain via huggingface model hub.

基于Bi-GRU + CRF 的中文机构名、人名识别, 支持google bert模型

Japanese IOB2 tagged corpus for Named Entity Recognition.

基于BI-LSTM+CRF的中文命名实体识别 Pytorch

Medical Concept Annotation Tool

Stanford CoreNLP: A Java suite of core NLP tools.