Triple
T14916168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pedestal Collection |
E371387
|
entity |
| Predicate | hasUpholsteryOption |
P49892
|
FINISHED |
| Object | fabric upholstery |
—
|
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: fabric upholstery | Statement: [Pedestal Collection, hasUpholsteryOption, fabric upholstery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUpholsteryOption Context triple: [Pedestal Collection, hasUpholsteryOption, fabric upholstery]
-
A.
upholsteryOption
chosen
Indicates the type or choice of upholstery applied to an item, such as a piece of furniture or vehicle interior.
-
B.
hasSeatMaterial
Indicates that an entity’s seat is made of, or covered with, a specified material.
-
C.
hasTypicalSeatColor
Indicates that an entity is characteristically associated with a particular color of seat.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
hasArmrestType
Indicates the specific style or configuration of armrests associated with an item.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded62038508190946499cd3552990e |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:31 a.m.