Triple
T7087524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 365 Everyday Value |
E165114
|
entity |
| Predicate | brandOwnerType |
P67912
|
FINISHED |
| Object | supermarket chain |
—
|
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: supermarket chain | Statement: [365 Everyday Value, brandOwnerType, supermarket chain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandOwnerType Context triple: [365 Everyday Value, brandOwnerType, supermarket chain]
-
A.
trademarkOwner
Indicates that one entity legally owns and holds the rights to a particular trademark associated with another entity or product.
-
B.
hasBrandType
chosen
Indicates that an entity is associated with or categorized under a particular brand type or classification.
-
C.
sponsorBrandType
Indicates the type or category of brand that is acting as a sponsor in the relationship.
-
D.
parentBrand
Indicates that one brand is the overarching or owning brand from which another brand is derived or subordinated.
-
E.
manufacturerType
Indicates the classification or category of a manufacturer based on its role, characteristics, or production type.
- 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_69c6887d98408190912b9580666b0c1d |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e513d9b08190a8a8d213c2264ce4 |
completed | March 27, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c172148190bf290c07bf579d1f |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:41 p.m.