Triple
T23801760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nirenberg problem |
E588691
|
entity |
| Predicate | metricTransformation |
P68295
|
FINISHED |
| Object | conformal deformation |
—
|
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: conformal deformation | Statement: [Nirenberg problem, metricTransformation, conformal deformation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metricTransformation Context triple: [Nirenberg problem, metricTransformation, conformal deformation]
-
A.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
B.
featuresTransformationOf
chosen
Indicates that something includes or presents a transformation or change applied to another entity.
-
C.
coordinateTransformation
Indicates a relationship where one coordinate system is mathematically converted or mapped into another, preserving the correspondence of points between them.
-
D.
settingOfTransformation
Indicates the place, context, or environment in which a transformation of an entity or state occurs.
-
E.
transformationProperty
Indicates that one entity has a specific behavior, constraint, or characteristic related to how it changes, converts, or is transformed into another form or state.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c74e430481909debd10c71785912 |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:53 p.m.