Triple
T6293606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli trials |
E141077
|
entity |
| Predicate | hasAssociatedRandomVariableType |
P38220
|
FINISHED |
| Object | Bernoulli random variable |
—
|
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: Bernoulli random variable | Statement: [Bernoulli trials, hasAssociatedRandomVariableType, Bernoulli random variable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedRandomVariableType Context triple: [Bernoulli trials, hasAssociatedRandomVariableType, Bernoulli random variable]
-
A.
hasVariabilityType
Indicates that an entity is associated with a specific kind or category of variability (e.g., how or in what way it varies).
-
B.
hasVariable
chosen
Indicates that one entity includes, defines, or is associated with a particular variable.
-
C.
hasDependentVariable
Indicates that one variable’s value is determined by, or functionally depends on, the value(s) of another variable or set of variables.
-
D.
hasVariance
Indicates that there is a measurable degree of variability or dispersion in the values or outcomes associated with the related entities.
-
E.
hasVarianceSymbol
Indicates that one entity is associated with, or represented by, a specific variance symbol in a mathematical or statistical context.
- 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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06438654481908c9833c5f0d61773 |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:27 p.m.