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中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、…
农业领域知识图谱的构建，包括数据爬取(百度百科)、数据分类、利用结构化数据生成三元组、非结构化数据的分句(LTP)，分词(jieba)，命名实体识别(LTP)、基于依存句法分析(主谓关系等)的关系抽取和利用neo4j生成可视化知识图谱
RoBERTa + BiLSTM + CRF for Chinese NER Task
根据自己搭的 LTP 服务器，实现：分词、词性标注、命名实体识别、依存句法分析、语义角色标、命名实体的抽取：人名，地名，机构名、三元组的抽取：主谓宾，动宾关系，介宾关系，（实体1，关系，实体2）
MiniCPM3-4B: An edge-side LLM that surpasses GPT-3.5-Turbo.
使用Bert+CRF、Bert+BiLSTM+CRF、Bert+BiGRU+CRF、Bert+BiGRU+self-atttention+CRF、AlBert+CRF、AlBert+BiLSTM+CRF、AlBert+BiGRU+CRF、AlBert+BiGRU+self-atttention+CRF进行命名实体等等
released code for our EMNLP22 paper: UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction
基于pytorch的中文三元组提取（命名实体识别+关系抽取）
2022 Tsinghua Data Mining Course Homework. Tmall repeat buyers prediction, 3 methods are used: XGboost, MLP, GraphSAGE
Pytorch reimplement of the paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction" ACL2020. The original code is written in keras.
Effective Cascade Dual-Decoder Model for Joint Entity and Relation Extraction.
The official gpt4free repository | various collection of powerful language models | o3 and deepseek r1, gpt-4.5
Reimplement CasRel model in PyTorch.使用PyTorch对吉林大学CasRel模型进行复现，并在百度关系抽取数据集上训练测试。
实体关系联合抽取模型/ My project on joint exraction of entities and relations
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。
Awesome Procedures On Cypher for Neo4j - codenamed "apoc" If you like it, please ★ above ⇧
利用pandas将excel中数据抽取，以三元组形式加载到neo4j数据库中构建相关知识图谱
Neo4j Movies Example application with Flask backend using the neo4j-python-driver
Natural Language Processing Tutorial for Deep Learning Researchers
bert-bilstm-crf implemented in pytorch for named entity recognition.
PyTorch solution of named entity recognition task Using Google AI's pre-trained BERT model.
Pytorch-Named-Entity-Recognition-with-transformers
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
A very simple framework for state-of-the-art Natural Language Processing (NLP)