shibing624 / relext
RelExt: A Tool for Relation Extraction from Text. 文本实体关系抽取工具。
☆50Updated 2 years ago
Alternatives and similar repositories for relext:
Users that are interested in relext are comparing it to the libraries listed below
- benchmark of KgCLUE, with different models and methods☆27Updated 3 years ago
- ☆57Updated 2 years ago
- 复习论文《A Frustratingly Easy Approach for Joint Entity and Relation Extraction》☆31Updated 3 years ago
- SinglepassTextCluster, an TextCluster tools based on Singlepass cluster algorithm that use tfidf vector and doc2vec,which can be used for…☆62Updated 3 years ago
- using lear to do ner extraction☆29Updated 3 years ago
- 基于pytorch的百度UIE命名实体识别 。☆57Updated 2 years ago
- [Unofficial] Predict code for AAAI 2022 paper: Unified Named Entity Recognition as Word-Word Relation Classification☆53Updated 2 years ago
- 句子匹配模型,包括无监督的SimCSE、ESimCSE、PromptBERT,和有监督的SBERT、CoSENT。☆98Updated 2 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 2 years ago
- 基于“Seq2Seq+前缀树”的知识图谱问答☆71Updated 3 years ago
- ccks金融事件主体抽取☆72Updated 4 years ago
- 百度2021年语言与智能技术竞赛多形态信息抽取赛道事件抽取部分torch版baseline☆76Updated 3 years ago
- pytorch Efficient GlobalPointer☆53Updated 3 years ago
- 使用多头的思想来进行命名实体识别☆33Updated 3 years ago
- GPLinker_pytorch☆81Updated 2 years ago
- 基于百度uie的关系抽取☆20Updated 2 years ago
- ☆87Updated 3 years ago
- WoBERT_pytorch☆40Updated 4 years ago
- 基于pytorch的GlobalPointer进行中文命名实体识别。☆36Updated last year
- 中文无监督SimCSE Pytorch实现☆134Updated 3 years ago
- Code for Label Semantics for Few Shot Named Entity Recognition☆56Updated last year
- CCKS 2020: 基于本体的金融知识图谱自动化构建技术评测☆90Updated 2 years ago
- ☆18Updated 3 years ago
- lic2020关系抽取比赛,使用Pytorch实现苏神的模型。☆101Updated 4 years ago
- GlobalPointer的优化版/NER实体识别☆118Updated 3 years ago
- 利用指针网络进行信息抽取,包含命名实体识别、关系抽取、事件抽取。☆123Updated 2 years ago
- Seq2seqAttGeneration, an basic implementation of text generation that using seq2seq attention model to generate poem series. this project…☆18Updated 4 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
- LLM for NER☆69Updated 8 months ago
- ☆42Updated 2 years ago