Triple
T22423039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erdős number concept |
E554296
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | collaboration distance measure |
C18166
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: collaboration distance measure Context triple: [Erdős number concept, instanceOf, collaboration distance measure]
-
A.
statistical distance
Statistical distance is a numerical measure of how different two probability distributions are, often used to quantify distinguishability or divergence between random variables or datasets.
-
B.
distance function
chosen
A distance function is a rule that assigns a non-negative real number to quantify how far apart two elements are in a given space, typically satisfying properties like non-negativity, identity, symmetry, and the triangle inequality.
-
C.
mathematical collaboration
Mathematical collaboration is the joint process by which mathematicians share ideas, methods, and insights to develop, refine, and communicate mathematical results that they might not achieve as effectively alone.
-
D.
collaborative networks
Collaborative networks are interconnected groups of individuals or organizations that share resources, knowledge, and responsibilities to achieve common goals more effectively than they could independently.
-
E.
multivariate dependence measure
A multivariate dependence measure is a quantitative function that assesses the strength and structure of statistical relationships among multiple random variables simultaneously, beyond simple pairwise associations.
- F. None of above.
Provenance (1 batch)
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. |
Created at: April 16, 2026, 8:47 p.m.