Triple
T2598870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balenciaga |
E58295
|
entity |
| Predicate | styleCharacteristics |
P20701
|
FINISHED |
| Object | sculptural volumes |
—
|
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: sculptural volumes | Statement: [Balenciaga, styleCharacteristics, sculptural volumes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: styleCharacteristics Context triple: [Balenciaga, styleCharacteristics, sculptural volumes]
-
A.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
B.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
C.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
D.
stylingFeature
chosen
Indicates a visual or design-related characteristic applied to an entity, such as formatting, layout, or aesthetic treatment.
-
E.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd4563b8c8190934616651e93654c |
completed | March 7, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69abd0d4e8648190b612eb09aa085451 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.