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  2. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  3. NebulaGraph - Wikipedia

    en.wikipedia.org/wiki/NebulaGraph

    NebulaGraph is a free software distributed graph database built for super large-scale graphs with milliseconds of latency. [1] NebulaGraph adopts the Apache 2.0 license and also comes with a wide range of data visualization tools.

  4. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    GraphRAG with a knowledge graph combining access patterns for unstructured, structured, and mixed data GraphRAG [ 40 ] (coined by Microsoft Research ) is a technique that extends RAG with the use of a knowledge graph (usually, LLM-generated) to allow the model to connect disparate pieces of information, synthesize insights, and holistically ...

  5. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Graph databases are a powerful tool for graph-like queries. For example, computing the shortest path between two nodes in the graph. Other graph-like queries can be performed over a graph database in a natural way (for example graph's diameter computations or community detection).

  6. Knowledge graph - Wikipedia

    en.wikipedia.org/wiki/Knowledge_graph

    In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...

  7. Ontotext - Wikipedia

    en.wikipedia.org/wiki/Ontotext

    Ontotext GraphDB (previously known as BigOWLIM) is a graph-based database [6] capable of working with knowledge graphs [7] produced by Ontotext, compliant with the RDF graph data model [8] and the SPARQL query language. [9] Some categorize it as a NoSQL database, meaning that it does not use tables like some other databases. [10]

  8. NoSQL - Wikipedia

    en.wikipedia.org/wiki/NoSQL

    Graph databases are designed for data whose relations are well represented as a graph consisting of elements connected by a finite number of relations. Examples of data include social relations, public transport links, road maps, network topologies, etc. Graph databases and their query language

  9. TerminusDB - Wikipedia

    en.wikipedia.org/wiki/TerminusDB

    TerminusDB is an open source knowledge graph and document store. It is used to build versioned data products. It is a native revision control database that is architecturally similar to Git. It is listed on DB-Engines. TerminusDB provides a document API for building via the JSON exchange format. It implements both GraphQL and a datalog variant ...