Triple
T7705103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolmogorov distance |
E174592
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | Kolmogorov–Smirnov test |
E174592
|
NE 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: Kolmogorov–Smirnov test | Statement: [Kolmogorov distance, usedIn, Kolmogorov–Smirnov test]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kolmogorov–Smirnov test Context triple: [Kolmogorov distance, usedIn, Kolmogorov–Smirnov test]
-
A.
Kruskal–Wallis test
The Kruskal–Wallis test is a nonparametric statistical method used to determine whether there are statistically significant differences between the medians of three or more independent groups.
-
B.
Fisher's exact test
Fisher's exact test is a statistical significance test used to determine whether there are nonrandom associations between two categorical variables in a contingency table, especially with small sample sizes.
-
C.
Tukey's honestly significant difference test
Tukey's honestly significant difference test is a statistical post-hoc procedure used to determine which specific group means differ after an ANOVA indicates a significant overall effect.
-
D.
Kolmogorov distance
chosen
Kolmogorov distance is a statistical metric that measures the maximum difference between two cumulative distribution functions, commonly used to quantify convergence in distribution and in goodness-of-fit tests.
-
E.
F-test
The F-test is a statistical hypothesis test used to compare variances and assess the overall significance of models, especially in analysis of variance (ANOVA) and regression.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6995b3e8c8190833108f883d5f53c |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7028f17f0819081686ac146750d3a |
completed | March 27, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8acc088148190ba5ba07e4ad2284c |
completed | March 29, 2026, 4:38 a.m. |
Created at: March 27, 2026, 4:03 p.m.