Triple

T19223413
Position Surface form Disambiguated ID Type / Status
Subject Makro (UK) E480674 entity
Predicate hasParentBrand P6092 FINISHED
Object Makro 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: Makro | Statement: [Makro (UK), hasParentBrand, Makro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makro
Context triple: [Makro (UK), hasParentBrand, Makro]
  • A. MACRO
    MACRO is an American media and entertainment company focused on producing and financing film and television projects that center Black people and other people of color.
  • B. MaK
    MaK is a German engineering and manufacturing company historically known for producing heavy machinery, locomotives, and military vehicles.
  • C. Makro (UK) chosen
    Makro (UK) is a British cash-and-carry wholesale chain serving businesses and trade customers, operating under the Booker Group.
  • D. Makossa
    Makossa is a popular urban dance and music style from Cameroon characterized by its infectious rhythms and hip-swaying movements.
  • E. the macroprosopus
    The Macroprosopus is a kabbalistic term for the transcendent, hidden aspect of the divine associated with the highest sefirah and the primordial divine countenance.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa95743481909314fd14e2c3d189 completed April 20, 2026, 10:06 a.m.
Created at: April 10, 2026, 1:24 p.m.