Triple
T22666614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson process |
E559807
|
entity |
| Predicate | hasStationaryIncrements |
P149162
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Poisson process, hasStationaryIncrements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationaryIncrements Context triple: [Poisson process, hasStationaryIncrements, true]
-
A.
hasStationaryMean
Indicates that the associated process or variable has a mean value that does not change over time.
-
B.
hasStationFunction
Indicates that an entity serves in a particular functional role or capacity at a station.
-
C.
hasIncrement
Indicates that one value or state increases by a specified step or amount relative to another.
-
D.
hasAutocorrelationFunction
Indicates that an entity is associated with a specific autocorrelation function describing how its values correlate with themselves over different time lags.
-
E.
hasMomentGeneratingFunction
Indicates that a random variable or probability distribution possesses a well-defined moment generating function characterizing all of its moments.
- F. None of above. chosen
Provenance (4 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781c2c808190baf6964ca1eced6f |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:09 p.m.