Triple

T1422253
Position Surface form Disambiguated ID Type / Status
Subject OWL Full E30248 entity
Predicate relatedStandard P37 FINISHED
Object OWL DL E165093 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: OWL DL | Statement: [OWL Full, relatedStandard, OWL DL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OWL DL
Context triple: [OWL Full, relatedStandard, OWL DL]
  • A. OWL DL chosen
    OWL DL is a sublanguage of the Web Ontology Language that balances expressive power with computational decidability by adhering closely to description logic foundations.
  • B. OWL
    OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
  • C. 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.
  • D. OWL 2 QL
    OWL 2 QL is a lightweight profile of the Web Ontology Language designed to enable efficient query answering over large datasets using standard relational database technologies.
  • E. OWL 2 EL
    OWL 2 EL is a lightweight profile of the Web Ontology Language designed for efficient reasoning over large-scale ontologies, particularly in domains like biomedical terminologies.
  • 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_69ad232534f48190b1392c2fba119b7c completed March 8, 2026, 7:20 a.m.
Created at: March 1, 2026, 8 p.m.