Triple
T23587271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernoulli distribution |
E582379
|
entity |
| Predicate | randomVariableType |
P24817
|
FINISHED |
| Object | binary 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: binary random variable | Statement: [Bernoulli distribution, randomVariableType, binary random variable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: randomVariableType Context triple: [Bernoulli distribution, randomVariableType, binary random variable]
-
A.
variableType
chosen
Indicates that one entity is the type or data category of the other entity, which is a variable.
-
B.
statisticalType
Indicates that one entity specifies the kind or category of statistical characterization or measurement that applies to another entity.
-
C.
naturalVariables
Indicates that certain variables or parameters arise directly from the inherent properties or natural behavior of a system, rather than being externally imposed or artificially defined.
-
D.
numericType
Indicates that one entity specifies or constrains the kind or category of numeric value associated with another entity.
-
E.
numberVariedBetween
Indicates that the numerical value associated with an entity changed across a specified range between two points or over a given period.
- 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.