changsha2999 / Rasa_neo4jLinks
基于Rasa 3.1.0 构建医疗领域的图谱型问答系统
☆22Updated 3 years ago
Alternatives and similar repositories for Rasa_neo4j
Users that are interested in Rasa_neo4j are comparing it to the libraries listed below
Sorting:
- 基于pytorch的百度UIE命名实体识别。☆56Updated 2 years ago
- 该仓库目的是实现基于知识图谱的中文问答系统☆57Updated 3 years ago
- 基于词汇信息融合的中文NER模型☆170Updated 3 years ago
- 基于GlobalPointer的实体/关系/事件抽取☆150Updated 3 years ago
- 基于PaddleNLP开源的抽取式UIE进行医学命名实体识别(torch实现)☆44Updated 3 years ago
- CCKS2020 面向中文短文本的实体链指任务。主要思路为:使用基于BiLSTM和Attention的语义模型进行Query和Doc的文本匹配,再针对匹配度进行pairwise排序,从而选出最优的知识库实体。☆47Updated 4 years ago
- https://tianchi.aliyun.com/dataset/dataDetail?dataId=95414☆30Updated 4 years ago
- using lear to do ner extraction☆29Updated 3 years ago
- ccks金融事件主体抽取☆74Updated 5 years ago
- “万创杯”中医药天池大数据竞赛——中医文献问题生成挑战 决赛 第一名方案☆138Updated 4 years ago
- [Unofficial] Predict code for AAAI 2022 paper: Unified Named Entity Recognition as Word-Word Relation Classification☆56Updated 3 years ago
- 基于bert_mrc的中文命名实体识别☆43Updated 3 years ago
- 基于汽车知识图谱的汽车问答多轮对话系统☆40Updated 6 years ago
- 使用torch整合两种经典的指针NER抽取范式,分别是SpanBert和苏神的GlobalPointer,简单加了些tricks,配置后一键运行☆134Updated last year
- GPLinker_pytorch☆86Updated 3 years ago
- 基于 pytorch 的 bert 实现和下游任务微调☆54Updated 3 years ago
- 法研杯2021类案检索赛道三等奖方案☆50Updated 3 years ago
- CMeEE/CBLUE/NER实体识别☆132Updated 3 years ago
- Cascade bert+word vec and one layer FLAT, trained by adversarial FGM and Stochastic Weight Averaging☆23Updated 4 years ago
- llama信息抽取实战☆101Updated 2 years ago
- 基于pytorch的GlobalPointer进行中文命名实体识别。☆37Updated 2 years ago
- GlobalPointer的优化版/NER实体识别☆122Updated 3 years ago
- Knowledge Graph☆176Updated 3 years ago
- bert-flat 简化版 添加了很多注释☆15Updated 4 years ago
- ☆57Updated 2 years ago
- NLP关系抽取:序列标注、层叠式指针网络、Multi-head Selection、Deep Biaffine Attention☆101Updated 4 years ago
- A full-process dialogue system that can be deployed online☆100Updated 3 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 5 years ago
- 2020 “万创杯”中医药天池大数据竞赛——中药说明书实体识别挑战 复盘☆31Updated 4 years ago
- Pytorch进行长文本分类。这里用到的网络有:FastText、TextCNN、TextRNN、TextRCNN、Transformer☆48Updated 5 years ago