Triple
T20627428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevanlinna–Pick interpolation |
E506854
|
entity |
| Predicate | solutionSetProperty |
P69697
|
FINISHED |
| Object | solution set is convex in the Schur class |
—
|
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: solution set is convex in the Schur class | Statement: [Nevanlinna–Pick interpolation, solutionSetProperty, solution set is convex in the Schur class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: solutionSetProperty Context triple: [Nevanlinna–Pick interpolation, solutionSetProperty, solution set is convex in the Schur class]
-
A.
solutionProperty
chosen
Indicates that a solution possesses a specific characteristic, attribute, or quality relevant to its behavior, composition, or performance.
-
B.
solutionType
Indicates the specific category or kind of solution associated with an entity or problem.
-
C.
solutionDeterminedBy
Indicates that the value or outcome of a solution is fully specified or fixed by the referenced factor(s) or condition(s).
-
D.
targetProperty
Indicates that one entity serves as the intended goal, focus, or object of another entity’s action, influence, or effect.
-
E.
setFeature
Indicates assigning or configuring a specific feature or property for an 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe645888190b639ebedc5b3041a |
completed | April 20, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:42 a.m.