Triple

T19703574
Position Surface form Disambiguated ID Type / Status
Subject Semantic MediaWiki E473153 entity
Predicate relatedTo P37 FINISHED
Object OWL NE NERFINISHED

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: OWL | Statement: [Semantic MediaWiki, relatedTo, OWL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OWL
Context triple: [Semantic MediaWiki, relatedTo, OWL]
  • A. OWL chosen
    OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
  • B. 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.
  • C. OWL 2 Web Ontology Language
    OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic 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. OWL 2 Full
    OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642b8707081908fbf96c989d2d52d completed April 20, 2026, 3:14 p.m.
Created at: April 10, 2026, 1:46 p.m.