Triple
T22666522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson integral |
E559805
|
entity |
| Predicate | kernelFormula |
P2310
|
FINISHED |
| Object | P_r(\theta) = \frac{1-r^2}{1-2r\cos\theta + r^2} |
—
|
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: P_r(\theta) = \frac{1-r^2}{1-2r\cos\theta + r^2} | Statement: [Poisson integral, kernelFormula, P_r(\theta) = \frac{1-r^2}{1-2r\cos\theta + r^2}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: kernelFormula
Context triple: [Poisson integral, kernelFormula, P_r(\theta) = \frac{1-r^2}{1-2r\cos\theta + r^2}]
-
A.
keyFormula
chosen
Indicates that a formula serves as the primary or defining expression associated with an entity or relationship.
-
B.
kernelType
Indicates the specific kind or category of kernel associated with or used by an entity.
-
C.
kernelOfProjectionFrom
Indicates the subset of elements that are mapped to zero (or the identity element) by a given projection map from one structure to another.
-
D.
formulaUsed
Indicates that a particular formula is employed or applied in performing a calculation, derivation, or reasoning step.
-
E.
hasGeneralFormula
Indicates that an entity (such as a class of compounds or expressions) is characterized by a general or canonical formula that represents all its specific instances.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781c2c808190baf6964ca1eced6f |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:09 p.m.