Triple
T10038295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chernoff information |
E205228
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | hypothesis testing performance measure |
C8696
|
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: hypothesis testing performance measure Context triple: [Chernoff information, instanceOf, hypothesis testing performance measure]
-
A.
statistical hypothesis test
A statistical hypothesis test is a formal procedure that uses sample data to evaluate the plausibility of a specified assumption (the null hypothesis) about a population parameter, typically by calculating a test statistic and comparing it to a reference distribution to decide whether to reject the null.
-
B.
statistical inference method
A statistical inference method is a systematic procedure for drawing conclusions about a population’s properties based on observed sample data, often quantifying uncertainty through probabilities or confidence measures.
-
C.
statistical procedure
A statistical procedure is a systematic method or set of steps used to collect, analyze, interpret, and draw conclusions from data based on principles of probability and statistics.
-
D.
statistical distance
chosen
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.
-
E.
nonparametric test
A nonparametric test is a statistical hypothesis test that does not assume a specific distribution for the population and instead relies on the ranks or signs of the data.
- 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
Created at: March 30, 2026, 8:55 p.m.