possible1402 Goto Github PK

amazon-weak-ner-needle

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

bert

TensorFlow code and pre-trained models for BERT

bond_coca

cluener2020

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

concept-graphs

Concept embedding and network analysis of scientific innovations emergence

delphi

Code and examples for "Learning on Knowledge Graph Dynamics Provides Early Warning of Impactful Research".

flair

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

git-tips

:octocat:Git常用命令集合

graphical_models

Implementation of inference and learning algorithms for various PGMs without standard libraries. Includes projects from the PGM specialization on Coursera offered by Stanford University.

hunflair-experiments

Source code of the HunFlair experiments

joyful-pandas

pandas中文教程

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

medicalnamedentityrecognition

Medical Named Entity Recognition implement using bi-directional lstm and crf model with char embedding.CCKS2017中文电子病例命名实体识别项目,主要实现使用了基于字向量的四层双向LSTM与CRF模型的网络.该项目提供了原始训练数据样本(一般醒目,出院情况,病史情况,病史特点,诊疗经过)与转换版本,训练脚本,预训练模型,可用于序列标注研究.把玩和PK使用.

named-entity-recognition-bidirectionallstm-cnn-conll

Keras implementation of "Few-shot Learning for Named Entity Recognition in Medical Text"

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）

national-science-exports

ner_incomplete_annotation

nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

nlp_chinese_corpus

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

partial_annotation_learning

protoner

Few-shot classification in Named Entity Recognition Task

python-project-blueprint

Blueprint/Boilerplate For Python Projects

semi-supervised-bert-ner

subwordslm

Unsupervised NER in chemical domain.

superalloydigger

The functions of superalloyDigger toolkit include batch downloading documents in XML and TXT format from the Elsevier database, locating target sentences from the full text and automatically extracting triple information in the form of <material name, property specifier, value>.