Triple

T1451769
Position Surface form Disambiguated ID Type / Status
Subject OWL 2 QL E31305 entity
Predicate relatedTo P37 FINISHED
Object RDF E29602 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: RDF | Statement: [OWL 2 QL, relatedTo, RDF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RDF
Context triple: [OWL 2 QL, relatedTo, RDF]
  • A. RDF chosen
    RDF (Resource Description Framework) is a standard model for data interchange on the Web that represents information as subject–predicate–object triples to enable structured, machine-readable metadata and knowledge graphs.
  • B. RDFS
    RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
  • C. OWL
    OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
  • D. Semantic Web
    The Semantic Web is an extension of the current web in which information is given well-defined meaning through standards like RDF and OWL, enabling machines to understand, share, and reason about data across different systems.
  • E. OWL DL
    OWL DL is a sublanguage of the Web Ontology Language that balances expressive power with computational decidability by adhering closely to description logic foundations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c57bc0908190a57e6bc3d20d5e3c completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1c9b7cac81909700821cb7f39a33 completed March 8, 2026, 6:52 a.m.
Created at: March 1, 2026, 8 p.m.