What is Knowledge Triple?
A knowledge triple is the fundamental unit of information in knowledge graphs, representing a single fact as a three-part structure: (subject, predicate, object). The subject is the entity the fact is about, the predicate describes the relationship or property, and the object is the value or entity the subject is related to. For example, (Albert Einstein, born_in, Germany) or (Water, boiling_point, 100°C) are knowledge triples.
This simple but powerful representation enables complex knowledge to be broken down into atomic facts that can be stored, queried, and combined. Triples can link together to form chains of reasoning: following (Alice, works_at, Company X) and (Company X, located_in, San Francisco) allows inferring information about Alice's location. The standardization of knowledge into triple format makes it possible to merge information from different sources and perform automated reasoning.
Knowledge triples are the building blocks of semantic web technologies and knowledge graph systems. They can be extracted from unstructured text using relation extraction techniques, manually curated by domain experts, or imported from structured data sources. Systems like RDF (Resource Description Framework) standardize how triples are represented and exchanged, while triple stores provide optimized databases for storing and querying large collections of triples. In agent systems, triples provide a structured memory format that supports precise retrieval and multi-hop reasoning.