Knowledge Graphs
Structured representations of entities and relationships.
A structured representation of knowledge that connects entities, their attributes, and relationships in a graph format to enable more intelligent data processing. Also known as Semantic Networks or Entity Graphs.
AI engines use knowledge graphs to ground their answers in facts rather than text patterns. Google's Knowledge Graph is the most-known example; AI engines build their own internal graphs from the structured data they crawl.
Knowledge graphs let AI systems reason over facts and relationships instead of matching text patterns. Because a graph stores entities and the connections between them, an AI engine can look up authoritative facts, follow the relationships between them, and ground its answer in verifiable knowledge rather than guessing. Content that maps cleanly onto these graphs - through consistent entity naming and explicit relationships - is more likely to be understood correctly and represented accurately in AI answers.
- Entity disambiguationHelping AI systems tell apart entities that share a name by anchoring each to distinct nodes and relationships.
- Fact groundingGiving AI engines a structured source of verifiable facts to consult before generating an answer, reducing the chance of an invented detail.
- Relationship reasoningLetting AI follow connections between entities - a company and its products, an author and their work - to answer questions that span multiple facts.
AI systems use knowledge graphs as a source of structured, verifiable facts to consult alongside what the model learned in training. When a query touches entities represented in a graph, the system can retrieve the relevant facts and relationships and ground its response in them, which improves factual accuracy. When an entity or relationship is missing from the graph, the model may fall back to ungrounded generation - which is why consistent, well-connected entity data is valuable.
Knowing the term is step one.
Geordy operationalizes every term in this glossary - generating the structured files AI engines actually read.