taorui-plus / OpenNRE
哈工大bert上fine turning ,中文人物关系抽取任务准确率0.97
☆118Updated 5 years ago
Alternatives and similar repositories for OpenNRE:
Users that are interested in OpenNRE are comparing it to the libraries listed below
- 基于远监督的中文关系抽取☆383Updated 3 years ago
- 限定领域的三元组抽取的一次尝试,本文将会介绍笔者在2019语言与智能技术竞赛的三元组抽取比赛方面的一次尝试。☆133Updated last year
- Code for http://lic2019.ccf.org.cn/kg 信息抽取。使用基于 BERT 的实体抽取和关系抽取的端到端的联合模型。☆286Updated 5 years ago
- 事件抽取相关算法汇总☆124Updated 5 years ago
- 2019百度的关系抽取比赛,使用Pytorch实现苏神的模型,F1在dev集可达到0.75,联合关系抽取,Joint Relation Extraction.☆313Updated 4 years ago
- 中文关系抽取☆135Updated 6 years ago
- 全局指针统一处理嵌套与非嵌套NER☆253Updated 3 years ago
- 实体识别和关系抽取的联合模型☆121Updated 6 years ago
- 一个关于百度2019语言与智能技术竞赛信息抽取 (http://lic2019.ccf.org.cn/kg) 模型, 模型采用BERT+CNN。DEMO地址 https://github.com/Wangpeiyi9979/InformationExtractionDem…☆187Updated 5 years ago
- 中文命名实体识别NER。用keras实现BILSTM+CRF、IDCNN+CRF、BERT+BILSTM+CRF进行实体识别。结果当然是BERT+BILSTM+CRF最好啦。☆286Updated 5 years ago
- CCKS 2020:新冠知识图谱构建与问答评测(四)新冠知识图谱问答评测☆215Updated 4 years ago
- Multiple-Relations-Extraction-Only-Look-Once. Just look at the sentence once and extract the multiple pairs of entities and their corresp…☆347Updated 5 years ago
- baidu aistudio event extraction competition☆224Updated last year
- Named Recognition Entity based on BERT and CRF 基于BERT+CRF的中文命名实体识别☆183Updated 2 years ago
- ☆454Updated 3 years ago
- SEBERTNets:一种面向金融领域的事件主体抽取方法☆193Updated 2 years ago
- Reject complicated operations for incorporating lexicon for Chinese NER.☆436Updated 3 years ago
- CCKS 2019 中文短文本实体链指比赛技术创新奖解决方案☆409Updated last year
- ccks2020 NER competitions☆116Updated 4 years ago
- albert + lstm + crf实体识别,pytorch实现。识别的主要实体是人名、地名、机构名和时间。albert + lstm + crf (named entity recognition)☆136Updated 2 years ago
- some baselines for lic2020 (http://lic2020.cipsc.org.cn/)☆218Updated 4 years ago
- 本项目是利用深度学习技术来构建知识图谱方向上的一次尝试,作为开放领域的关系抽取,算是笔者的一次创新,目前在这方面的文章和项目都很少。☆305Updated last year
- 中文关系抽取☆94Updated 3 years ago
- 事件知识图谱构建相关的论文, 包含事件抽取、事件关系识别等任务☆82Updated last year
- 本项目用于展示三元组抽取后形成的知 识图谱,包括几本小说的实体关系,以及README.md,介绍这方面的一篇文章。☆192Updated 4 years ago
- A trial of kbqa based on bert for NLPCC2016/2017 Task 5 (基于BERT的中文知识库问答实践,代码可跑通)☆270Updated 5 years ago
- Comparison of Chinese Named Entity Recognition Models between NeuroNER and BertNER☆328Updated 5 years ago
- chinese-sequence-ner多模型中文命名实体识别☆75Updated 4 years ago
- NLP关系抽取:序列标注、层叠式指针网络、Multi-head Selection、Deep Biaffine Attention☆100Updated 3 years ago
- 本NER项目包含多个中文数据集,模型采用BiLSTM+CRF、BERT+Softmax、BERT+Cascade、BERT+WOL等,最后用TFServing进行模型部署,线上推理和线下推理。☆80Updated 3 years ago