Editing Knowledge Graphs (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Entity''' — A distinct real-world object or concept represented as a node: a person (Albert Einstein), an organization (NASA), a concept (Relativity).
* '''Relationship (predicate)''' — A typed, directed connection between two entities: "bornIn," "worksFor," "isA," "hasCapital."
* '''Triple''' — The fundamental unit of a knowledge graph: (Subject, Predicate, Object). Example: (Albert_Einstein, bornIn, Ulm).
* '''RDF (Resource Description Framework)''' — A W3C standard for representing knowledge graph triples using URIs.
* '''SPARQL''' — The query language for RDF knowledge graphs, analogous to SQL for relational databases.
* '''Ontology''' — A formal specification of concepts, categories, and relationships within a domain; defines the schema of a knowledge graph.
* '''OWL (Web Ontology Language)''' — A W3C language for defining ontologies with rich semantic constraints.
* '''Property Graph''' — An alternative KG model where nodes and edges can have attributes (key-value pairs). Used in Neo4j.
* '''Cypher''' — The query language for property graph databases like Neo4j.
* '''Knowledge Graph Embedding''' — Representing entities and relations as vectors in a continuous space for machine learning over KGs.
* '''Link prediction''' — The task of inferring missing relationships in a knowledge graph from existing ones.
* '''Entity alignment''' — Matching entities across two different knowledge graphs that refer to the same real-world object.
* '''Named Entity Recognition (NER)''' — The NLP task of identifying entities in text; first step in knowledge graph construction from text.
* '''Relation extraction''' — Identifying the relationship between two named entities in text; used in automated KG construction.
* '''Wikidata''' — A free, multilingual, community-maintained knowledge graph with hundreds of millions of triples.
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