Triple
T32816688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kesten–Stigum theorem |
E839311
|
entity |
| Predicate | involvesRandomVariable |
P29140
|
FINISHED |
| Object | generation size Zₙ |
—
|
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: generation size Zₙ | Statement: [Kesten–Stigum theorem, involvesRandomVariable, generation size Zₙ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesRandomVariable Context triple: [Kesten–Stigum theorem, involvesRandomVariable, generation size Zₙ]
-
A.
introducesRandomnessIn
Indicates that something adds an element of unpredictability or variability into another process, system, or outcome.
-
B.
stochastic
chosen
Indicates that the relationship or process involves randomness or probabilistic behavior rather than being fully deterministic.
-
C.
pseudoVariantInvolves
Indicates that a pseudo-variant (an inferred or non-canonical variant representation) functionally involves or corresponds to a particular underlying variant or set of variants.
-
D.
usesVAR
Indicates that one entity makes use of, employs, or utilizes another entity as a variable or resource in performing some function or operation.
-
E.
hasCauseOfVariability
Indicates a relationship where one factor or condition is identified as the source or driver of variation observed in another.
- 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: May 1, 2026, 1:15 a.m.