Triple
T22423097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erdős–Kac theorem |
E554297
|
entity |
| Predicate | varianceAsymptotic |
P91243
|
FINISHED |
| Object | log log n |
—
|
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: log log n | Statement: [Erdős–Kac theorem, varianceAsymptotic, log log n]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: varianceAsymptotic Context triple: [Erdős–Kac theorem, varianceAsymptotic, log log n]
-
A.
hasVariance
Indicates that there is a measurable degree of variability or dispersion in the values or outcomes associated with the related entities.
-
B.
hasAsymptotics
chosen
Indicates that one entity describes or determines the asymptotic behavior or growth rate of another entity, typically in a limiting or large-scale sense.
-
C.
hasVarianceSymbol
Indicates that one entity is associated with, or represented by, a specific variance symbol in a mathematical or statistical context.
-
D.
eigenvalueStatistics
Indicates that one entity characterizes or provides information about the distribution or behavior of the eigenvalues associated with another entity.
-
E.
usesVAR
Indicates that one entity makes use of, employs, or utilizes another entity as a variable or resource in performing some function or operation.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2af620819083338127e78137dc |
completed | April 29, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:47 p.m.