Triple

T16271674
Position Surface form Disambiguated ID Type / Status
Subject Belinda McDonald E395013 entity
Predicate familyName P18 FINISHED
Object McDonald E163973 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: McDonald | Statement: [Belinda McDonald, familyName, McDonald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: McDonald
Context triple: [Belinda McDonald, familyName, McDonald]
  • A. McDonald chosen
    McDonald is a common Scottish-origin surname borne by numerous notable individuals across politics, sports, academia, and entertainment.
  • B. McDonaldland
    McDonaldland is a whimsical, fictional world used in McDonald's advertising, populated by Ronald McDonald and a cast of colorful mascot characters.
  • C. Kroc
    Kroc is a surname most famously associated with Ray Kroc, the American businessman who built McDonald's into a global fast-food empire.
  • D. Mayor McCheese
    Mayor McCheese is a McDonaldland character depicted as a cheeseburger-headed mayor who appears in McDonald's advertising alongside Ronald McDonald.
  • E. Big Mac
    Big Mac was the popular nickname for Denver’s McNichols Sports Arena, a former multi-purpose indoor venue that hosted the NBA’s Denver Nuggets, NHL’s Colorado Avalanche, and numerous major events.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2460a4f7c8190a614c11f7eaa0a7a completed April 17, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017bf09888190b3d90db3517a2f1e completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:05 a.m.