Triple
T31683234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tête de Maure |
E808589
|
entity |
| Predicate | hasStylisticForm |
P137145
|
FINISHED |
| Object | silhouette |
—
|
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: silhouette | Statement: [Tête de Maure, hasStylisticForm, silhouette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStylisticForm Context triple: [Tête de Maure, hasStylisticForm, silhouette]
-
A.
hasStructuralStyle
Indicates that one entity possesses, exhibits, or is characterized by a particular architectural or structural design style.
-
B.
stylisticElement
chosen
Indicates a relationship where one entity functions as a stylistic feature, device, or characteristic that shapes the expressive or aesthetic quality of another entity.
-
C.
stylisticRange
Indicates the range or spectrum of styles that characterize or can be applied to something.
-
D.
stylisticQuality
Indicates the relationship in which one entity characterizes or evaluates the manner, style, or expressive quality of another entity or work.
-
E.
hasStyleCharacteristics
Indicates that one entity exhibits or embodies the stylistic features, traits, or qualities 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69feced53a7c819098ec474fb7d514b0 |
completed | May 9, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69fecd9cd5288190aac8b4e04a7ee78e |
completed | May 9, 2026, 6:01 a.m. |
Created at: April 30, 2026, 11:05 p.m.