Triple
T26731069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fosse |
E673974
|
entity |
| Predicate | featuresSignatureStyleElement |
P14486
|
FINISHED |
| Object | turned-in knees |
—
|
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: turned-in knees | Statement: [Fosse, featuresSignatureStyleElement, turned-in knees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSignatureStyleElement Context triple: [Fosse, featuresSignatureStyleElement, turned-in knees]
-
A.
featuresStyleElement
Indicates that one entity includes or incorporates a particular style-related element as part of its composition or design.
-
B.
hasSignatureVisualStyle
chosen
Indicates that an entity is characterized by a distinctive and recognizable visual style that sets it apart from others.
-
C.
featuresStyle
Indicates that one entity exhibits, incorporates, or is characterized by a particular style associated with another entity.
-
D.
signatureStyle
Indicates the characteristic way in which an entity typically signs its name or marks documents, distinguishing its unique signing pattern or format.
-
E.
stylingFeature
Indicates a visual or design-related characteristic applied to an entity, such as formatting, layout, or aesthetic treatment.
- 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: April 27, 2026, 3:45 a.m.