Triple

T10607893
Position Surface form Disambiguated ID Type / Status
Subject McQueen E275923 entity
Predicate variantOf P4680 FINISHED
Object MacQueen E850582 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: MacQueen | Statement: [McQueen, variantOf, MacQueen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MacQueen
Context triple: [McQueen, variantOf, MacQueen]
  • A. Macqueen chosen
    Macqueen is a surname of Scottish origin borne by various notable individuals across fields such as sports, arts, and public life.
  • B. MacRae
    MacRae is a Scottish surname associated with various notable individuals in fields such as entertainment, sports, and public life.
  • C. John McKenzie
    John McKenzie was a prominent professional ice hockey right winger best known for his successful career in the NHL and WHA during the 1960s and 1970s.
  • D. Turnbull
    Turnbull is a Scottish-origin surname borne by various notable figures, including Australian politician and former prime minister Malcolm Turnbull.
  • E. Mott
    Mott is a surname most notably associated with Sir Nevill Mott, the Nobel Prize–winning British physicist recognized for his work on the electronic structure of magnetic and disordered systems.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df4c38c881908f69bb757b8e03f5 completed April 8, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95eb726bc8190a8db7357bd126016 completed April 10, 2026, 8:33 p.m.
Created at: April 8, 2026, 7:32 p.m.