Triple

T1422226
Position Surface form Disambiguated ID Type / Status
Subject OWL Full E30248 entity
Predicate compatibleWith P203 FINISHED
Object RDF Schema E29939 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 Schema | Statement: [OWL Full, compatibleWith, RDF Schema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RDF Schema
Context triple: [OWL Full, compatibleWith, RDF Schema]
  • A. RDFS chosen
    RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
  • B. RDF
    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.
  • 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. OWL Full
    OWL Full is the most expressive and semantically unrestricted variant of the Web Ontology Language, allowing full RDF compatibility at the cost of computational decidability.
  • E. SKOS
    SKOS (Simple Knowledge Organization System) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and subject headings on the Semantic Web.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4915bfc8190a631330b7c495b49 completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08b09c948190a5ec17021299049e completed March 8, 2026, 5:27 a.m.
Created at: March 1, 2026, 8 p.m.