Top 162 ner open source projects

中文人名语料库。人名生成器。中文姓名,姓氏,名字,称呼,日本人名,翻译人名,英文人名。可用于中文分词、人名实体识别。

PyTorch solution of named entity recognition task Using Google AI's pre-trained BERT model.

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

Natural Language Toolkit for bahasa Malaysia, https://malaya.readthedocs.io/

Ner with Bert

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

NER toolkit for HTML data

😋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）。

Datasets to train supervised classifiers for Named-Entity Recognition in different languages (Portuguese, German, Dutch, French, English)

Named Entity Recognition based on dictionaries

MONPA 罔拍是一個提供正體中文斷詞、詞性標註以及命名實體辨識的多任務模型

ML data annotations made super easy for teams. Just upload data, add your team and build training/evaluation dataset in hours.

ChineseNER based on BERT, with BiLSTM+CRF layer

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。

پیکره بزرگ شناسایی موجودیت‌های نامدار فارسی برچسب خورده

a sklearn wrapper for Google's BERT model

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.

Jiagu深度学习自然语言处理工具 知识图谱关系抽取 中文分词 词性标注 命名实体识别 情感分析 新词发现 关键词 文本摘要 文本聚类

Named Entity Recognition (LSTM + CRF) - Tensorflow

Embedding, NMT, Text_Classification, Text_Generation, NER etc.

面向中文电子病历的命名实体识别

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

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。

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

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

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.

Medical Concept Annotation Tool

BNLP is a natural language processing toolkit for Bengali Language.

Named Entity Recognition (NER) Annotation tool for SpaCy. Generates Traning Data as a JSON which can be readily used.

An implementation of a full named-entity evaluation metrics based on SemEval'13 Task 9 - not at tag/token level but considering all the tokens that are part of the named-entity

搜索所有中文NLP数据集，附常用英文NLP数据集

My solution to the Natural Language Processing course made by Dan Jurafsky, Chris Manning in Winter 2012.

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

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

datagrand 2019 information extraction competition rank9

Papers and Book to look at when starting NLP 📚

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%。

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

Lexicon-based Named Entity Recognition

reference tensorflow code for named entity tagging

BOND: BERT-Assisted Open-Domain Name Entity Recognition with Distant Supervision

Named Entity Recognition (NER) task using Bi-LSTM-CRF model implemented in Tensorflow 2.0(tensorflow2.0 +)

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

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

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.

CCKS2019评测任务五-公众公司公告信息抽取，第3名

Bert-base NLP pipeline for Turkish, Ner, Sentiment Analysis, Question Answering etc.

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

瑞金医院MMC人工智能辅助构建知识图谱大赛-baseline

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

reference pytorch code for named entity tagging

PhoNLP: A BERT-based multi-task learning toolkit for part-of-speech tagging, named entity recognition and dependency parsing (NAACL 2021)

LSTM-CRF for NER with ConLL-2002 dataset

Use Google's BERT for named entity recognition （CoNLL-2003 as the dataset）.

End-to-end neural relation extraction using deep biaffine attention (ECIR 2019)

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

PyTorch repository for text categorization and NER experiments in Turkish and English.

DeFactoNLP: An Automated Fact-checking System that uses Named Entity Recognition, TF-IDF vector comparison and Decomposable Attention models.

Multilingual Meta-Embeddings for Named Entity Recognition (RepL4NLP & EMNLP 2019)