Triple
T11858936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Look silhouette |
E282110
|
entity |
| Predicate | typicalWaistTreatment |
P86094
|
FINISHED |
| Object | tight waist cinching |
—
|
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: tight waist cinching | Statement: [New Look silhouette, typicalWaistTreatment, tight waist cinching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWaistTreatment Context triple: [New Look silhouette, typicalWaistTreatment, tight waist cinching]
-
A.
waistlinePosition
Indicates the relative vertical placement of a garment’s waistline on the body (e.g., high, natural, or low).
-
B.
bodyTreatment
Indicates a treatment or therapeutic procedure that is applied to a person's body.
-
C.
typicalFit
chosen
Indicates that one entity is a usual, expected, or characteristic match or correspondence for another in a given context.
-
D.
exportTreatment
Indicates the action or process of sending or transferring a treatment (such as a medical, data, or procedural treatment) from one system, location, or context to another for external use or application.
-
E.
curdTreatment
Indicates a treatment or process applied to curd, such as a specific method, condition, or handling used in its preparation or modification.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69a099c8190a674db64c50eca5a |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.