Triple
T3499682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DKNY (licensed watches) |
E73933
|
entity |
| Predicate | typicalPriceSegment |
P18022
|
FINISHED |
| Object | mid-range |
—
|
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: mid-range | Statement: [DKNY (licensed watches), typicalPriceSegment, mid-range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPriceSegment Context triple: [DKNY (licensed watches), typicalPriceSegment, mid-range]
-
A.
priceCategory
chosen
Indicates the classification of an item or service based on its price level or cost range.
-
B.
priceDeterminedBy
Indicates that the price of one entity is set, influenced, or calculated based on another entity or factor.
-
C.
typicalSegmentType
Indicates that something is classified as belonging to a usual or characteristic type of segment within a broader structure or sequence.
-
D.
priceInfluencedBy
Indicates that the price of one entity is affected or determined by another specified factor or entity.
-
E.
pricingStrategy
Indicates the approach or method used to set, adjust, or structure prices for products or services in a given context.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd4eb308190b84e84261ceec229 |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0cd8b0819099da300af09880da |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.