Triple
T2325288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ornstein–Uhlenbeck process |
E48273
|
entity |
| Predicate | hasStationaryDistribution |
P9754
|
FINISHED |
| Object | normal distribution |
—
|
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: normal distribution | Statement: [Ornstein–Uhlenbeck process, hasStationaryDistribution, normal distribution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationaryDistribution Context triple: [Ornstein–Uhlenbeck process, hasStationaryDistribution, normal distribution]
-
A.
hasDistributionFunction
chosen
Indicates that an entity is associated with a specific distribution function that characterizes how its values or occurrences are probabilistically or statistically distributed.
-
B.
isStable
Indicates that the state, condition, or configuration of an entity does not change significantly over time or under expected variations in its environment.
-
C.
convergenceProperty
Indicates that one entity has a convergence-related characteristic or behavior with respect to another entity, such as approaching a limit or stabilizing under repeated application.
-
D.
hasMomentGeneratingFunction
Indicates that a random variable or probability distribution possesses a well-defined moment generating function characterizing all of its moments.
-
E.
hasGroundState
Indicates that an entity possesses a lowest-energy, most stable state in its energy configuration.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:50 p.m.