Triple
T15961349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kruskal–Wallis test |
E387065
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Kruskal–Wallis H test |
E387065
|
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: Kruskal–Wallis H test | Statement: [Kruskal–Wallis test, alsoKnownAs, Kruskal–Wallis H test]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kruskal–Wallis H test Context triple: [Kruskal–Wallis test, alsoKnownAs, Kruskal–Wallis H test]
-
A.
Kruskal–Wallis test
chosen
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.
Dunnett's test
Dunnett's test is a multiple comparison statistical procedure used to compare several treatment groups directly against a single control group while controlling the overall type I error rate.
-
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.
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.
-
E.
McNemar
McNemar is a surname most notably associated with Richard McNemar, an early 19th-century American Shaker leader and religious writer.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156ff4cdc81908db31394eaa191bc |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe827d248190adbfd41f55638ebd |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.