Triple
T17752936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson distribution with P(s) = e^{-s} |
E443155
|
entity |
| Predicate | isContinuous |
P128217
|
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 distribution with P(s) = e^{-s}, isContinuous, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isContinuous
Context triple: [Poisson distribution with P(s) = e^{-s}, isContinuous, true]
-
A.
canBeContinuous
Indicates that something has the potential to occur, exist, or be maintained without interruption over a continuous range or period.
-
B.
timeContinuousOrDiscrete
Indicates whether the time dimension in a given context is modeled as a continuous flow or as discrete, separate time points.
-
C.
hasRepresentationContinuity
Indicates that one entity maintains a consistent or continuous representational relationship with another across time, context, or state changes.
-
D.
continuityType
Indicates the specific manner or pattern in which continuity is maintained or transitions occur between related elements or states.
-
E.
hasContinuousSequence
Indicates that there exists an unbroken, ordered sequence or range connecting the related entities without gaps.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841c0540819093a32d759775c61f |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3cfab7edc8190b663282d565a0389 |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:10 a.m.