Triple
T15797516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën 15 Six |
E383018
|
entity |
| Predicate | stylist |
P120057
|
FINISHED |
| Object | Flaminio Bertoni |
—
|
NE NERFINISHED |
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: Flaminio Bertoni | Statement: [Citroën 15 Six, stylist, Flaminio Bertoni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stylist Context triple: [Citroën 15 Six, stylist, Flaminio Bertoni]
-
A.
styledCelebrity
Indicates that one entity (typically a stylist or source) is responsible for selecting or creating the fashion or appearance of a celebrity.
-
B.
styleFor
Indicates a relationship where one entity defines, specifies, or is used as the style or styling configuration applied to another entity.
-
C.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
D.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
E.
stylisticFocus
Indicates a relationship where something is primarily concerned with, emphasizes, or is characterized by a particular style or set of stylistic features.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4def80481908f72733ce9133bc6 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e00537bd1c81908d6e832792fd934f |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e006b17f7881908b8c7a37f0af4581 |
completed | April 15, 2026, 9:44 p.m. |
Created at: April 10, 2026, 4:48 a.m.