Triple
T35238080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IGA (Canada) |
E1017429
|
entity |
| Predicate | isFranchiseModel |
P182646
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [IGA (Canada), isFranchiseModel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFranchiseModel Context triple: [IGA (Canada), isFranchiseModel, true]
-
A.
hasFranchiseModel
Indicates that one entity operates under, offers, or is associated with a business franchise system or structure defined by another entity.
-
B.
isNationalFranchiseFor
Indicates that one entity operates as the nationally recognized franchise counterpart or branch for another entity.
-
C.
hasFranchiseRelation
Indicates a relationship where one entity holds franchise rights or operates under the brand, business model, or authorization of another entity.
-
D.
isTraditionalFranchiseIn
Indicates that a franchise operates in a given location under a traditional (standard, non-specialized) franchise agreement.
-
E.
hasFranchiseRepresentation
Indicates that one entity serves as an official franchise representative or outlet for 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_69f76de235048190b990070c23c51b6b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7904a770481908ef3f788e51e8dba |
completed | May 3, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:02 p.m.