Triple
T22666630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson process |
E559807
|
entity |
| Predicate | hasInterarrivalTimesMean |
P28047
|
FINISHED |
| Object | 1/λ |
—
|
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: 1/λ | Statement: [Poisson process, hasInterarrivalTimesMean, 1/λ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterarrivalTimesMean Context triple: [Poisson process, hasInterarrivalTimesMean, 1/λ]
-
A.
hasMeanSpacing
Indicates the average distance or interval between repeated or adjacent elements in a pattern, structure, or arrangement.
-
B.
hasStationaryMean
Indicates that the associated process or variable has a mean value that does not change over time.
-
C.
hasInterval
Indicates that something is associated with a specific span or range between two points in time, space, or value.
-
D.
isHeavyTailed
Indicates that a distribution has a high probability of extreme values, with tails that decay more slowly than those of an exponential or normal distribution.
-
E.
averageRecurrenceInterval
chosen
Indicates the typical time span between successive occurrences of the same type of event.
- 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_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. |
Created at: April 17, 2026, 3:09 p.m.