ARDUJS / Event-Extration
2020语言与智能技术竞赛:事件抽取任务
☆27Updated 4 years ago
Alternatives and similar repositories for Event-Extration:
Users that are interested in Event-Extration are comparing it to the libraries listed below
- 百度2020语言与智能技术竞赛:事件抽取赛道方案代码☆53Updated 4 years ago
- 2020语言与智能技术竞赛:事件抽取任务 -- 联合抽取baseline☆54Updated 4 years ago
- CCKS 2020: 面向中文短文本的实体链指任务☆43Updated 3 years ago
- ACE2005事件抽取数据预处理☆55Updated 4 years ago
- 实现了一下multi-head-selection联合关系实体抽取☆30Updated 5 years ago
- 端到端的基于知识图谱的问答系统,分为实体识别和关系分类两部,在BERT基础上做多任务联合训练。☆30Updated 5 years ago
- 2020语言与智能技术竞赛:关系抽取任务(https://aistudio.baidu.com/aistudio/competition/detail/31?lang=zh_CN)☆24Updated 4 years ago
- CCKS2020面向金融领域的小样本跨类迁移事件抽取baseline☆55Updated 2 years ago
- 2020语言与智能技术竞赛:事件抽取任务方案代码☆28Updated 2 years ago
- 2019百度语言与智能技术竞赛信息抽取赛代5名代码☆69Updated 5 years ago
- 使用ACE2005创建以事件和实体为节点的事件知识图谱,用于智能问答☆16Updated 5 years ago
- lic2020关系抽取比赛,使用Pytorch实现苏神的模型。☆101Updated 4 years ago
- ccks2021事件抽取比赛☆30Updated 3 years ago
- 使用多头的思想来进行命名实体识别☆33Updated 3 years ago
- 本项目是CCKS2020实体链指比赛baseline(pytorch)☆18Updated 4 years ago
- CCKS 2020:面向金融领域的小样本跨类迁移事件抽取。该项目实现基于MRC的事件抽取方法☆39Updated 2 years ago
- ACE 2005 corpus preprocessing for Event Extraction task☆50Updated 4 years ago
- ☆29Updated 5 years ago
- The source code of 《 FGN:Fusion Glyph Network for Chinese Named Entity Recognition 》. SOTA Chinese NER method fusing both glyph represne…☆50Updated 4 years ago
- BDCI2019-互联网金融新实体发现-第7名(本可top3)☆18Updated 5 years ago
- 通用kbqa,训练数据来源于ccks2018和2019,图谱数据爬取于百度百科☆24Updated 4 years ago
- Baidu lic 2020 event extraction☆9Updated 4 years ago
- using lear to do ner extraction☆29Updated 3 years ago
- ccks2020基于本体的金融知识图谱自动化构建技术评测第五名方法总结☆50Updated 2 years ago
- Chinese NER using BiLSTM/BERT + CRF☆65Updated 3 years ago
- ccks金融事件主体抽取☆72Updated 4 years ago
- 2020语言与智能技术竞赛:关系抽取任务☆65Updated 4 years ago
- 本项目是NLP领域一些任务的基准模型实现,包括文本分类、命名实体识别、实体关系抽取、NL2SQL、CKBQA以及BERT的各种下游任务应用。☆47Updated 4 years ago
- ☆18Updated 3 years ago
- multi-label,classifier,text classification,多标签文本分类,文本分类,BERT,ALBERT,multi-label-classification,seq2seq,attention,beam search☆32Updated 2 years ago