Triple
T8225532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global indicator framework for the Sustainable Development Goals and targets of the 2030 Agenda for Sustainable Development |
E192164
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | global statistical framework |
C9120
|
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: global statistical framework Context triple: [Global indicator framework for the Sustainable Development Goals and targets of the 2030 Agenda for Sustainable Development, instanceOf, global statistical framework]
-
A.
statistical framework
chosen
A statistical framework is a structured set of principles, assumptions, and methods that guides how data are collected, modeled, analyzed, and interpreted to draw valid inferences about underlying phenomena.
-
B.
global statistical system
A global statistical system is an integrated framework of institutions, standards, methods, and technologies that collectively produce, share, and govern comparable statistical data across countries and international organizations.
-
C.
global reference frame
A global reference frame is a fixed, overarching coordinate system used to consistently define positions, orientations, and motions of objects throughout an entire modeled world or environment.
-
D.
scaling framework
A scaling framework is a structured approach that defines the principles, processes, and tools needed to grow a system, organization, or product efficiently and sustainably as demand increases.
-
E.
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.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
Created at: March 30, 2026, 5:45 p.m.