Triple

T7971069
Position Surface form Disambiguated ID Type / Status
Subject Individual Lightning Lane purchases E185322 entity
Predicate languageUsedInMarketing P64853 FINISHED
Object à la carte 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: à la carte | Statement: [Individual Lightning Lane purchases, languageUsedInMarketing, à la carte]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageUsedInMarketing
Context triple: [Individual Lightning Lane purchases, languageUsedInMarketing, à la carte]
  • A. languageUsedAs
    Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
  • B. languagesUsed
    Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
  • C. primaryLanguageMarket chosen
    Indicates that a particular language is the main or dominant language used within a given market or market segment.
  • D. languageUsedInTrade
    Indicates that a particular language is employed as a medium of communication in trade or commercial transactions between parties.
  • E. languageSpecifies
    Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
  • F. None of above.

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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bd476108190988a75653a5c56d6 completed March 31, 2026, 3:13 a.m.
PD Predicate disambiguation batch_69cb047a8e4c81909b79e0f0bf56440c completed March 30, 2026, 11:17 p.m.
Created at: March 30, 2026, 5:13 p.m.