Triple
T38114398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corolle collection |
E951750
|
entity |
| Predicate | garmentTypeIncluded |
P15063
|
FINISHED |
| Object | tailored jackets |
—
|
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: tailored jackets | Statement: [Corolle collection, garmentTypeIncluded, tailored jackets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: garmentTypeIncluded Context triple: [Corolle collection, garmentTypeIncluded, tailored jackets]
-
A.
garmentType
chosen
Indicates the specific kind or category of garment associated with an entity.
-
B.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
C.
clothingFeature
Indicates that one entity has a specific clothing-related attribute, detail, or characteristic associated with it.
-
D.
fashionItem
Indicates that one entity is a fashion-related product or accessory associated with, used by, or worn by another entity.
-
E.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
- 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:21 p.m.