30 open-source projects similar to accenture/ampligraph, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best AmpliGraph alternative.
OpenKE is a knowledge graph embedding framework designed to transform structured knowledge graphs into low-dimensional vector representations. It functions as a library for representation learning and a toolset for converting entities and relations into numerical embeddings. The project includes a link prediction engine to evaluate the likelihood of relationships between entities and identify missing facts in large-scale graphs. It provides a dedicated preprocessing tool to map raw entity and relation strings into numerical identifiers for machine learning training. The framework's capabilit
Starspace is a vector embedding framework designed for training high-dimensional representations of text and images. It functions as a machine learning system for neural ranking, text classification, and knowledge graph embedding, mapping different object types into a shared numerical space to facilitate retrieval and prediction tasks. The system includes specialized tools for knowledge graph completion and link prediction by representing entities and their relationships within a multi-relational vector space. It further provides capabilities for semantic content recommendation and large-scal
FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge graph construction tool and a GraphRAG knowledge store, integrating structured property graphs with vector search to provide grounded context for large language models. The engine is designed as a multi-tenant graph engine, capable of hosting thousands of isolated datasets within a single instance. The system distinguishes itself by using linear algebra for query execution, treating relationship tensors as matrix multiplications to achieve low-latency multi-hop traversals. It ut
DGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks
Implementation of caption-image retrieval from the paper "Order-Embeddings of Images and Language"
利用网络上公开的数据构建一个小型的证券知识图谱/知识库
自然语言处理、知识图谱、对话系统,大模型等技术研究与应用。
AbstractKnowledgeGraph, a systematic knowledge graph that concentrate on abstract thing including abstract entity and action. 抽象知识图谱,目前规模50万,支持名词性实体、状态性描述、事件性动作进行抽象。目标于抽象知识,包括抽象实体,抽象动作,抽象事件。基于该知识图谱,可以进行不同层级的实体抽象和动作抽象,这与人类真实高度概括的认知是一致的。
Causality event extraction demo project including casual patterns and experiment on large scale corpus. 基于因果关系知识库的因果事件图谱实验项目,本项目罗列了因果显式表达的几种模式,基于这种模式和大规模语料,再经过融合等操作,可形成因果事件图谱。
An experiment and demo-level tool for text information extraction (event-triples extraction), which can be a route to the event chain and topic graph, 基于依存句法与语义角色标注的事件三元组抽取,可用于文本理解如文档主题链,事件线等应用。
ChinesePersonRelationGraph, person relationship extraction based on nlp methods.中文人物关系知识图谱项目,内容包括中文人物关系图谱构建,基于知识库的数据回标,基于远程监督与bootstrapping方法的人物关系抽取,基于知识图谱的知识问答等应用。
Text Content Grapher based on keyinfo extraction by NLP method。输入一篇文档,将文档进行关键信息提取,进行结构化,并最终组织成图谱组织形式,形成对文章语义信息的图谱化展示。
Code for experiments in the AAAI 2016 paper "Holographic Embeddings of Knowledge Graphs"
KnowledgeGraphCourse is a structured collection of graduate-level academic materials, lecture notes, and a comprehensive curriculum focused on the theory and application of knowledge graphs. It serves as a markdown-based educational resource that provides navigable course modules and study guides. The material covers specialized research on integrating knowledge graphs with large language models to reduce hallucinations. It includes detailed guides on using the SPARQL language for storing large-scale graph datasets and executing optimized queries. The curriculum spans a broad range of capabi
Jiagu深度学习自然语言处理工具 知识图谱关系抽取 中文分词 词性标注 命名实体识别 情感分析 新词发现 关键词 文本摘要 文本聚类
KnowledgeGraphData is a collection of structured datasets and corpora designed to provide a foundational layer for cognitive intelligence and artificial intelligence systems. It primarily consists of large-scale Chinese knowledge graph datasets, including entity-relation data and NLP training sets used to drive semantic understanding and automated question answering. The project focuses on the construction and export of massive entity-attribute-value graphs, organizing knowledge into portable formats. It provides specialized domain partitioning to tailor information retrieval for professional
USING BERT FOR Attribute Extraction in KnowledgeGraph. fine-tuning and feature extraction. 使用基于bert的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取。
Knowledge Graph Embeddings including TransE, TransH, TransR and PTransE
Source code for experiments in the papers "Complex Embeddings for Simple Link Prediction" (ICML 2016) and "Knowledge Graph Completion via Complex Tensor Factorization" (JMLR 2017).
Current methods for knowledge graph (KG) representation learning focus solely on the structure of the KG and do not exploit any kind of external information, such as visual and linguistic information corresponding to the KG entities. In this paper, we propose a multimodal translation-based…