Triple
T35734954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panthère jewelry collection |
E1032861
|
entity |
| Predicate | craftsmanshipFeature |
P183868
|
FINISHED |
| Object | pavé diamond setting |
—
|
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: pavé diamond setting | Statement: [Panthère jewelry collection, craftsmanshipFeature, pavé diamond setting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: craftsmanshipFeature Context triple: [Panthère jewelry collection, craftsmanshipFeature, pavé diamond setting]
-
A.
craftsmanshipLevel
Indicates the degree or quality of skill and care applied in creating or executing something.
-
B.
craftsmanshipReputation
Indicates the recognized quality and reliability of an entity’s workmanship as perceived by others.
-
C.
traditionalCraft
Indicates that an entity is associated with or practices a craft or skill that is rooted in long-established, culturally transmitted traditions.
-
D.
craftSpecialty
Indicates that an entity has a particular area of specialized skill or focus within a craft or artisanal practice.
-
E.
craftedIn
Indicates that an object or work was created or produced at a particular place or within a specific location.
- 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_69f76e10e59081908d81ad9ce22f40b6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a34e80dc8190980d5b7b0b91341d |
completed | May 3, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4:05 p.m.