Triple
T3428510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAG Heuer Carrera |
E72281
|
entity |
| Predicate | associatedBrandCollection |
P48668
|
FINISHED |
| Object | TAG Heuer Carrera collection |
—
|
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: TAG Heuer Carrera collection | Statement: [TAG Heuer Carrera, associatedBrandCollection, TAG Heuer Carrera collection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedBrandCollection Context triple: [TAG Heuer Carrera, associatedBrandCollection, TAG Heuer Carrera collection]
-
A.
relatedBrand
Indicates a relationship where one brand is associated with, connected to, or otherwise related to another brand.
-
B.
associatedBrandCategory
Indicates that a brand is linked to or classified under a particular product or service category.
-
C.
distributedBrand
Indicates that one entity serves as a distributor or reseller for the brand of another entity.
-
D.
parentBrand
Indicates that one brand is the overarching or owning brand from which another brand is derived or subordinated.
-
E.
referencesBrand
Indicates that one entity mentions, cites, or otherwise refers to a specific brand in its content or context.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb983f4608190abcc27aa7b926deb |
completed | March 8, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69adadfea024819094b41a13bc004bda |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb00f4f8c81908f88daf71f6a9c29 |
completed | March 8, 2026, 5:21 p.m. |
Created at: March 8, 2026, 3:15 p.m.