Triple
T23587190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli differential equation |
E582378
|
entity |
| Predicate | canBeTransformedInto |
P2463
|
FINISHED |
| Object | linear first-order differential equation |
—
|
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: linear first-order differential equation | Statement: [Bernoulli differential equation, canBeTransformedInto, linear first-order differential equation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeTransformedInto Context triple: [Bernoulli differential equation, canBeTransformedInto, linear first-order differential equation]
-
A.
canTransform
Indicates that one entity is capable of being changed or converted into another entity or state.
-
B.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
C.
transformedIn
Indicates that one entity has been changed, converted, or altered into another state, form, or representation within a specific context or process.
-
D.
canBe
chosen
Indicates that one entity has the potential, permission, or capability to become, perform as, or be classified as another entity.
-
E.
convertsTo
Indicates that one entity is transformed or changed into another entity, typically resulting in a different state, form, or representation.
- 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_69e248f8d8248190acd5aee77f0d1709 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b03195748190b7e34f334902ac93 |
completed | April 29, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:41 p.m.