Triple
T3499674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DKNY (licensed watches) |
E73933
|
entity |
| Predicate | licensedProductType |
P48520
|
FINISHED |
| Object | watches |
—
|
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: watches | Statement: [DKNY (licensed watches), licensedProductType, watches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: licensedProductType Context triple: [DKNY (licensed watches), licensedProductType, watches]
-
A.
licenseFamily
Indicates that one license belongs to, is derived from, or is categorized under a broader family or class of related licenses.
-
B.
licenseManufacturerOf
Indicates that one entity is authorized, via a license, to manufacture products or goods on behalf of or under the rights of another entity.
-
C.
licenseBuiltIn
Indicates that a license is inherently included within or comes standard as part of another product, service, or system rather than being added separately.
-
D.
licenseModel
Indicates the licensing scheme or framework that governs how something may be used, distributed, or accessed.
-
E.
licenseBuiltAs
Indicates that one entity is constructed, configured, or deployed under the terms or identity of another entity’s license.
- 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_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. |
| PDg | Predicate description generation | batch_69adaef1037c819082c7af949ec85360 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:18 p.m.