Triple
T10607963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bumster trousers |
E275924
|
entity |
| Predicate | silhouetteEffect |
P40118
|
FINISHED |
| Object | lowered visual waistline |
—
|
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: lowered visual waistline | Statement: [bumster trousers, silhouetteEffect, lowered visual waistline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: silhouetteEffect Context triple: [bumster trousers, silhouetteEffect, lowered visual waistline]
-
A.
hasSilhouetteShape
chosen
Indicates that one entity has the overall outline or contour shape specified or characterized by another entity.
-
B.
introducedSilhouette
Indicates that one entity caused another entity to first appear or be presented in outline or partial form, rather than in full detail.
-
C.
visualSimplicity
Indicates that something is characterized by a minimal, uncluttered, and easy-to-perceive visual appearance or design.
-
D.
spatialEffect
Indicates a spatial relationship where one entity affects or alters the position, arrangement, or spatial properties of another.
-
E.
featuresInversion
Indicates that one entity exhibits or incorporates an inversion of another entity, such as a reversed, mirrored, or otherwise inverted form or structure.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4c38c881908f69bb757b8e03f5 |
completed | April 8, 2026, 11:05 p.m. |
| PD | Predicate disambiguation | batch_69d6dd72c1288190adbb5e79e94c044a |
completed | April 8, 2026, 10:57 p.m. |
Created at: April 8, 2026, 7:32 p.m.