Triple
T23189127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Wren Scott |
E579681
|
entity |
| Predicate | fashionLabelSpecialty |
P151295
|
FINISHED |
| Object | figure-hugging dresses |
—
|
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: figure-hugging dresses | Statement: [L'Wren Scott, fashionLabelSpecialty, figure-hugging dresses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fashionLabelSpecialty Context triple: [L'Wren Scott, fashionLabelSpecialty, figure-hugging dresses]
-
A.
fashionLabel
Indicates that an entity is a fashion brand or label associated with the design, production, or marketing of clothing or accessories.
-
B.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
C.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
D.
fashionReputation
Indicates the perceived status or esteem an entity holds within the context of fashion, based on how its style, taste, or influence is judged by others.
-
E.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
- F. None of above. chosen
Provenance (4 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fd592248190a7e705c554885cd1 |
completed | April 29, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b75e2708190ba48875e36f983bc |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:05 p.m.