Hierarchy-Aware Global Model for Hierarchical Text Classification

Code and models for the paper "Aspect Sentiment Classification with Aspect-Specific Opinion Spans", EMNLP 2020.

Source code for "Head-Driven Phrase Structure Grammar Parsing on Penn Treebank" published at ACL 2019

Sequence-to-Nuggets: Nested Entity Mention Detection via Anchor-Region Networks

Codes for the paper Bipartite Flat-Graph Network for Nested Named Entity Recognition

Code for EMNLP 2019 paper "A Boundary-aware Neural Model for Nested Named Entity Recognition"

Named Entity Recognition as Dependency Parsing

Named Entity Recognition for Chinese social media (Weibo). From EMNLP 2015 paper.

Source code and dataset for NAACL 2019 paper "Adversarial Training for Weakly Supervised Event Detection".

A list of NLP resources focused on event extraction task

基于法律裁判文书的事件抽取及其应用，包括数据的分词、词性标注、命名实体识别、事件要素抽取和判决结果预测等内容

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

This repository aims to track the progress in BioNER and give a related paper list and an overview of the state-of-the-art (SOTA).

Lexicon-based Named Entity Recognition

This is the repository of paper "low-resource Name Tagging Learned with Weakly Labeled Data" accepted at EMNLP 2019

Reject complicated operations for incorporating lexicon for Chinese NER.

A Neural Multi-digraph Model for Chinese NER with Gazetteers

Label-Specific Document Representation for Multi-Label Text Classification

中文自然语言处理 (NLP) 标注工具，与 有志之士 共同 促进 中文 自然语言处理 的 发展。

中文自然语言处理 (NLP) 标注工具，与 有志之士 共同 促进 中文 自然语言处理 的 发展。

中文自然语言处理数据集，平时做做实验的材料。欢迎补充提交合并。

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

Code for the COLING 2018 paper "Document-level Multi-aspect Sentiment Classification by Jointly Modeling Users, Aspects, and Overall Ratings"

📧 Implement Naive Bayes and Adaboost from scratch and use them to filter spam emails.

python实现基于贝叶斯的简单垃圾邮件分类

Crime assistant including crime type prediction and crime consult service based on nlp methods and crime kg,罪名法务智能项目,内容包括856项罪名知识图谱, 基于280万罪名训练库的罪名预测,基于20W法务问答对的13类问题分类与法律资讯问答功能.

对收集的法律文档进行一系列分析，包括根据规范自动切分、案件相似度计算、案件聚类、法律条文推荐等（试验目前基于婚姻类案件，可扩展至其它领域）。