Triple
T24805956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runge phenomenon |
E620658
|
entity |
| Predicate | typicalExampleFunction |
P108356
|
FINISHED |
| Object | Runge function f(x) = 1 / (1 + 25 x^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: Runge function f(x) = 1 / (1 + 25 x^2) | Statement: [Runge phenomenon, typicalExampleFunction, Runge function f(x) = 1 / (1 + 25 x^2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalExampleFunction Context triple: [Runge phenomenon, typicalExampleFunction, Runge function f(x) = 1 / (1 + 25 x^2)]
-
A.
typicalFunction
Indicates that something serves as the usual or characteristic function or role of an entity.
-
B.
typicalFunctionClass
Indicates that something belongs to the usual or characteristic functional category associated with it.
-
C.
typicalExpressionExample
Indicates that the given expression is a representative or characteristic example of how something is typically expressed or formulated.
-
D.
exampleType
Indicates that one entity serves as a representative or illustrative instance of the type or category defined by another entity.
-
E.
standardExample
chosen
Indicates that something is a typical or canonical instance used to illustrate a general case or concept.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 18, 2026, 4:50 a.m.