Triple

T9779548
Position Surface form Disambiguated ID Type / Status
Subject Burque E237330 entity
Predicate hasAlternativeNicknameForSameCity P39 FINISHED
Object Duke City E233730 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: Duke City | Statement: [Burque, hasAlternativeNicknameForSameCity, Duke City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Duke City
Context triple: [Burque, hasAlternativeNicknameForSameCity, Duke City]
  • A. Duke City chosen
    Duke City is a popular nickname for Albuquerque, New Mexico, reflecting its historical ties to Spanish nobility.
  • B. Frisco
    Frisco is the popular nickname for the historic St. Louis–San Francisco Railway, a major American railroad that operated across the Midwest and South.
  • C. Charlotte
    Charlotte is a royal figure bearing the traditional title of Princess Royal, historically associated with the eldest daughter of the British monarch.
  • D. Charlotte
    Charlotte is a feminine given name of French and English origin, traditionally used as the female form of Charles and borne by numerous queens, nobles, and notable figures.
  • E. Charlotte
    Charlotte is a prominent American professional wrestler best known for her championship success in WWE and for being the daughter of wrestling legend Ric Flair.
  • 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_69ca84d975a08190aab25b02a89bdab3 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda13663f081909b95563038eb6485 completed April 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bd28b0e48190984cf44d88f324d7 completed April 5, 2026, 1:38 a.m.
Created at: March 30, 2026, 8:27 p.m.