Triple
T2664235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie Savoy |
E55594
|
entity |
| Predicate | wardrobeStyle |
P36462
|
FINISHED |
| Object | sensual and bohemian clothing |
—
|
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: sensual and bohemian clothing | Statement: [Annie Savoy, wardrobeStyle, sensual and bohemian clothing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wardrobeStyle Context triple: [Annie Savoy, wardrobeStyle, sensual and bohemian clothing]
-
A.
wardrobeFeature
Indicates that a wardrobe possesses or includes a specific feature, attribute, or functional element.
-
B.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
C.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
D.
notableOutfit
chosen
Indicates that an entity is known for or associated with wearing a particular outfit or style of clothing.
-
E.
dressFeature
Indicates that a dress possesses or is characterized by a particular feature, attribute, or design element.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96dba44819085c3e651afba7806 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.