Triple

T28575387
Position Surface form Disambiguated ID Type / Status
Subject Burger King E723224 entity
Predicate menuAdaptation P164649 FINISHED
Object localization to regional tastes LITERAL 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: localization to regional tastes | Statement: [Burger King, menuAdaptation, localization to regional tastes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: menuAdaptation
Context triple: [Burger King, menuAdaptation, localization to regional tastes]
  • A. menuType
    Indicates the classification or category of a menu (e.g., main menu, context menu, settings menu) associated with an interface or system.
  • B. menuDesign
    Indicates the relationship in which one entity defines or specifies the layout, structure, or visual arrangement of another entity’s menu.
  • C. menuItemType
    Indicates the relationship between a menu item and the type or category it belongs to (e.g., appetizer, main course, dessert).
  • D. menuPath
    Indicates the hierarchical navigation route or sequence of menu items used to access a particular option or function within a menu system.
  • E. mayAdapt
    Indicates that one entity is permitted or allowed to modify, adjust, or alter another entity.
  • F. None of above. chosen

Provenance (4 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_69f01d7e97708190ae9e77ee66a68abd completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f650c7d5ac81908b1764972e438168 completed May 2, 2026, 7:30 p.m.
PD Predicate disambiguation batch_69f64cb0d8008190912e1430cfaf92aa completed May 2, 2026, 7:12 p.m.
PDg Predicate description generation batch_69f64db8ee1881909362701d72ffe282 completed May 2, 2026, 7:17 p.m.
Created at: April 28, 2026, 4:12 a.m.