Triple
T11858932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Look silhouette |
E282110
|
entity |
| Predicate | typicalSkirtShape |
P68143
|
FINISHED |
| Object | A-line |
—
|
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: A-line | Statement: [New Look silhouette, typicalSkirtShape, A-line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSkirtShape Context triple: [New Look silhouette, typicalSkirtShape, A-line]
-
A.
typicalFit
Indicates that one entity is a usual, expected, or characteristic match or correspondence for another in a given context.
-
B.
typicalBodyType
Indicates that one entity is the usual or characteristic body type associated with another entity.
-
C.
fashionCharacteristic
chosen
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
D.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
E.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
- 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.