Triple
T8640826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erdős–Rényi model |
E204641
|
entity |
| Predicate | asymptoticDegreeDistribution |
P9486
|
FINISHED |
| Object | Poisson distribution for sparse regime |
—
|
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: Poisson distribution for sparse regime | Statement: [Erdős–Rényi model, asymptoticDegreeDistribution, Poisson distribution for sparse regime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: asymptoticDegreeDistribution Context triple: [Erdős–Rényi model, asymptoticDegreeDistribution, Poisson distribution for sparse regime]
-
A.
minimumDegree
Indicates that the relationship specifies the smallest number of connections or edges incident to any entity within a given structure or set.
-
B.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
-
C.
derivativeDistribution
Indicates a relationship where one entity is a financial derivative whose value or payoff is contractually based on, or distributed according to, the performance or characteristics of another underlying entity.
-
D.
distributedAs
chosen
Indicates that something is allocated, delivered, or spread out according to a particular pattern, rule, or distribution scheme.
-
E.
classDistribution
Indicates how instances are proportionally or numerically distributed across different classes or categories within a dataset or grouping.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47944d1c819081f448f14d04bf9d |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.