Triple
T13590926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loro Piana |
E324688
|
entity |
| Predicate | textileUse |
P74917
|
FINISHED |
| Object | fabrics for luxury tailoring houses |
—
|
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: fabrics for luxury tailoring houses | Statement: [Loro Piana, textileUse, fabrics for luxury tailoring houses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textileUse Context triple: [Loro Piana, textileUse, fabrics for luxury tailoring houses]
-
A.
textileFeature
Indicates a characteristic, property, or notable aspect associated with a textile or fabric.
-
B.
textileType
chosen
Indicates the specific kind or category of textile material associated with an entity.
-
C.
usesDyes
Indicates that one entity employs or applies dyes in relation to another entity or process.
-
D.
typicalFabric
Indicates that something is made from or associated with a fabric material that is standard or characteristic for its type.
-
E.
fiberwiseDescription
Indicates a description or characterization that is given separately for each fiber in a fibered or parameterized structure, specifying how the relationship or action behaves over individual fibers.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb056ce088190a6feb4266633d18b |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.