Triple
T25728616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volterra integral equation |
E645176
|
entity |
| Predicate | canBeDiscretizedBy |
P52986
|
FINISHED |
| Object | Galerkin methods |
—
|
NE NERFINISHED |
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: Galerkin methods | Statement: [Volterra integral equation, canBeDiscretizedBy, Galerkin methods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeDiscretizedBy Context triple: [Volterra integral equation, canBeDiscretizedBy, Galerkin methods]
-
A.
canBeContinuous
Indicates that something has the potential to occur, exist, or be maintained without interruption over a continuous range or period.
-
B.
discretizes
chosen
Indicates that one entity converts or partitions another entity into a finite set of discrete parts, intervals, or categories.
-
C.
hasDiscreteVersion
Indicates that one entity exists as a specific, separate version or edition of another entity.
-
D.
canBeDissectedBy
Indicates that one entity is capable of being divided or analyzed into parts by another entity or method.
-
E.
timeContinuousOrDiscrete
Indicates whether the time dimension in a given context is modeled as a continuous flow or as discrete, separate time points.
- 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 21, 2026, 11:09 p.m.