Triple
T6065038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tareyton |
E135134
|
entity |
| Predicate | hasAdvertisingVisual |
P68438
|
FINISHED |
| Object | smokers with black eyes |
—
|
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: smokers with black eyes | Statement: [Tareyton, hasAdvertisingVisual, smokers with black eyes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdvertisingVisual Context triple: [Tareyton, hasAdvertisingVisual, smokers with black eyes]
-
A.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
B.
usesAdvertisingModel
Indicates that one entity employs or relies on another entity’s advertising-based business or revenue model.
-
C.
hasSignageType
Indicates the specific category or kind of signage associated with an object, location, or entity.
-
D.
hasMarketingIcon
Indicates that an entity is associated with, or represented by, a specific marketing-related icon or symbol.
-
E.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity of 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05723c91c819090b4d4672e72f9f3 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:10 p.m.