Triple

T29661531
Position Surface form Disambiguated ID Type / Status
Subject Fiddler, Fifer & Practical Cafe E750418 entity
Predicate hasFranchisePartner P121664 FINISHED
Object Starbucks 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: Starbucks | Statement: [Fiddler, Fifer & Practical Cafe, hasFranchisePartner, Starbucks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFranchisePartner
Context triple: [Fiddler, Fifer & Practical Cafe, hasFranchisePartner, Starbucks]
  • A. hasFranchiseConnection
    Indicates a relationship where two entities are linked through a franchise arrangement, such as licensing, branding, or operational affiliation within the same franchise system.
  • B. participatingFranchise
    Indicates that a franchise is involved as a participant in a particular program, event, or arrangement.
  • C. hasFranchiseRepresentation
    Indicates that one entity serves as an official franchise representative or outlet for another entity.
  • D. hasPartner
    Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
  • E. hasFranchiseRelation chosen
    Indicates a relationship where one entity holds franchise rights or operates under the brand, business model, or authorization of another entity.
  • 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_69f0d62418a08190a401b127adf9f8a6 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f6bbf6e33c819086e5176d64e7a614 completed May 3, 2026, 3:07 a.m.
PD Predicate disambiguation batch_69f6ba6b1e6c8190adf9d6a257e0b744 completed May 3, 2026, 3 a.m.
Created at: April 28, 2026, 6:58 p.m.