Triple
T4092316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khinchin–Kahane type inequalities |
E87730
|
entity |
| Predicate | usesRandomVariables |
P29140
|
FINISHED |
| Object | Rademacher random variables |
—
|
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: Rademacher random variables | Statement: [Khinchin–Kahane type inequalities, usesRandomVariables, Rademacher random variables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesRandomVariables Context triple: [Khinchin–Kahane type inequalities, usesRandomVariables, Rademacher random variables]
-
A.
hasVariability
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
B.
usesVAR
Indicates that one entity makes use of, employs, or utilizes another entity as a variable or resource in performing some function or operation.
-
C.
hasVariance
Indicates that there is a measurable degree of variability or dispersion in the values or outcomes associated with the related entities.
-
D.
hasIndependentVariable
Indicates that one entity functions as the independent variable that influences or determines another entity in a relationship or experiment.
-
E.
stochastic
chosen
Indicates that the relationship or process involves randomness or probabilistic behavior rather than being fully deterministic.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefcae22a081908af65a960306b78c |
completed | March 9, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:40 p.m.