Triple

T8926601
Position Surface form Disambiguated ID Type / Status
Subject Sequential Analysis E212551 entity
Predicate influencedBy P9 FINISHED
Object Neyman–Pearson hypothesis testing framework E212555 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: Neyman–Pearson hypothesis testing framework | Statement: [Sequential Analysis, influencedBy, Neyman–Pearson hypothesis testing framework]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neyman–Pearson hypothesis testing framework
Context triple: [Sequential Analysis, influencedBy, Neyman–Pearson hypothesis testing framework]
  • A. Neyman–Pearson theory of hypothesis testing chosen
    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.
  • B. 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.
  • C. Sequential Analysis
    Sequential Analysis is a foundational statistical methodology that develops procedures for evaluating data as it is collected, allowing decisions to be made at variable sample sizes rather than after a fixed number of observations.
  • D. Statement on p-values and statistical significance
    The "Statement on p-values and statistical significance" is a landmark American Statistical Association document that clarifies the proper use and interpretation of p-values and cautions against their misuse in scientific research and decision-making.
  • E. Cramér–Rao bound
    The Cramér–Rao bound is a fundamental result in statistical estimation theory that gives a lower limit on the variance of any unbiased estimator of a parameter, characterizing the best possible precision achievable.
  • 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_69ca839481d48190b42b037e0d0f636c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6671557c81909f3837ffd6a15ffe completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba58e9ec81909141c516d05ac790 completed April 3, 2026, 1:02 p.m.
Created at: March 30, 2026, 6:57 p.m.