Triple

T18034269
Position Surface form Disambiguated ID Type / Status
Subject Mary Lou McDonald E431466 entity
Predicate familyName P18 FINISHED
Object McDonald NE NERFINISHED

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: [Mary Lou McDonald, familyName, McDonald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: McDonald
Context triple: [Mary Lou 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 (2 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_69d8b9050fb48190890155145deb0a66 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4be38766c8190ae95701f4575469c completed April 19, 2026, 11:36 a.m.
Created at: April 10, 2026, 10:25 a.m.