Triple

T3758969
Position Surface form Disambiguated ID Type / Status
Subject Library of Congress Linked Data Service E82115 entity
Predicate usesStandard P1587 FINISHED
Object OWL E4407 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 | Statement: [Library of Congress Linked Data Service, usesStandard, OWL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OWL
Context triple: [Library of Congress Linked Data Service, usesStandard, 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 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. 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.
  • E. 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.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc20b20819095fedf803aadc53a completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e5133ba48190a18ea170e3b9e1cd completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:35 p.m.