Triple
T23587239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli distribution |
E582379
|
entity |
| Predicate | standardDeviation |
P92092
|
FINISHED |
| Object | sqrt(p(1-p)) |
—
|
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: sqrt(p(1-p)) | Statement: [Bernoulli distribution, standardDeviation, sqrt(p(1-p))]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardDeviation Context triple: [Bernoulli distribution, standardDeviation, sqrt(p(1-p))]
-
A.
hasStandardDeviationSymbol
Indicates that a given notation, variable, or symbol is used to represent the standard deviation in a statistical context.
-
B.
statValue
chosen
Indicates that an entity has a particular statistical attribute with a specified value.
-
C.
relativeStandardUncertainty
Indicates the ratio of a measurement’s standard uncertainty to the measured value, expressing uncertainty relative to the magnitude of the quantity.
-
D.
standardNumber
Indicates that an entity is associated with a canonical or officially recognized reference number used for identification or classification.
-
E.
statisticsConsidered
Indicates that certain statistics are taken into account or used as a basis in a decision, analysis, or evaluation involving the related entities.
- 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.