Triple

T8359641
Position Surface form Disambiguated ID Type / Status
Subject Hotelling’s T-squared distribution E196772 entity
Predicate hasStatistic P3976 FINISHED
Object Hotelling’s T-squared statistic 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 statistic | Statement: [Hotelling’s T-squared distribution, hasStatistic, Hotelling’s T-squared statistic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hotelling’s T-squared statistic
Context triple: [Hotelling’s T-squared distribution, hasStatistic, Hotelling’s T-squared statistic]
  • 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. 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.
  • 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. Neyman–Pearson theory of hypothesis testing
    The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
  • E. Statistical Decision Functions
    Statistical Decision Functions is a foundational work in decision theory and statistics that systematically develops the theory of optimal decision-making under uncertainty.
  • 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_69ce1d0a3ba481909a8c247c4c476104 completed April 2, 2026, 7:38 a.m.
Created at: March 30, 2026, 6 p.m.