Triple
T2731236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itô process |
E60316
|
entity |
| Predicate | hasCoefficient |
P29146
|
FINISHED |
| Object | drift coefficient |
—
|
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: drift coefficient | Statement: [Itô process, hasCoefficient, drift coefficient]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoefficient Context triple: [Itô process, hasCoefficient, drift coefficient]
-
A.
coefficientProperty
chosen
Indicates a relationship where one entity serves as a coefficient or scalar factor that quantitatively modifies or characterizes another entity or property.
-
B.
firstCoefficientProperty
Indicates a property or characteristic specifically associated with the first coefficient in a mathematical or algebraic expression.
-
C.
hasCouplingConstant
Indicates that one entity is associated with a specific coupling constant value that quantifies the strength of an interaction or relationship.
-
D.
hasDerivative
Indicates that one entity is derived, obtained, or produced from another through some transformation, process, or modification.
-
E.
hasCovarianceStructure
Indicates that one entity possesses or is associated with a specific covariance structure that characterizes how its variables co-vary.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaee29088190bc4c734e48995794 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82586f88190a98f60d3247fe2d3 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.