Triple
T8359595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Hotelling |
E196771
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Hotelling's T-squared test |
E196772
|
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: Hotelling's T-squared test | Statement: [Harold Hotelling, knownFor, Hotelling's T-squared test]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hotelling's T-squared test Context triple: [Harold Hotelling, knownFor, Hotelling's T-squared test]
-
A.
Hotelling’s T-squared distribution
chosen
Hotelling’s T-squared distribution is a multivariate generalization of Student’s t-distribution used primarily for hypothesis testing and constructing confidence regions for mean vectors in multivariate statistics.
-
B.
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.
-
C.
Student’s t-distribution
Student’s t-distribution is a continuous probability distribution used primarily to estimate population means and conduct hypothesis tests when sample sizes are small and population variance is unknown.
-
D.
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.
-
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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb807134008190b4671326e0414210 |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde7bd74fc8190abdb2813d51d79f8 |
completed | April 2, 2026, 3:51 a.m. |
Created at: March 30, 2026, 6 p.m.