Triple

T1762687
Position Surface form Disambiguated ID Type / Status
Subject Harold Hotelling E38691 entity
Predicate notableWork P4 FINISHED
Object Hotelling’s T-squared distribution
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.
E196772 NE FINISHED

How this triple was built (4 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 distribution | Statement: [Harold Hotelling, notableWork, Hotelling’s T-squared distribution]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hotelling’s T-squared distribution
Context triple: [Harold Hotelling, notableWork, Hotelling’s T-squared distribution]
  • A. Frisch–Waugh–Lovell theorem
    The Frisch–Waugh–Lovell theorem is a fundamental result in econometrics that shows how the coefficients of a multiple linear regression can be obtained by first partialling out (regressing out) other explanatory variables.
  • B. 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.
  • C. Edgeworth expansion
    Edgeworth expansion is an asymptotic series that refines the central limit theorem by providing higher-order approximations to the distribution of normalized sums of random variables.
  • D. Gaussian distribution
    The Gaussian distribution, also known as the normal distribution, is a fundamental continuous probability distribution characterized by its symmetric bell-shaped curve and central role in statistics and the natural sciences.
  • E. Procrustes
    Procrustes is a figure from Greek mythology known as a cruel bandit who mutilated travelers to force them to fit his iron bed, until he was slain by the hero Theseus.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hotelling’s T-squared distribution
Triple: [Harold Hotelling, notableWork, Hotelling’s T-squared distribution]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hotelling’s T-squared distribution
Target entity description: 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.
  • A. Frisch–Waugh–Lovell theorem
    The Frisch–Waugh–Lovell theorem is a fundamental result in econometrics that shows how the coefficients of a multiple linear regression can be obtained by first partialling out (regressing out) other explanatory variables.
  • B. 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.
  • C. Edgeworth expansion
    Edgeworth expansion is an asymptotic series that refines the central limit theorem by providing higher-order approximations to the distribution of normalized sums of random variables.
  • D. Gaussian distribution
    The Gaussian distribution, also known as the normal distribution, is a fundamental continuous probability distribution characterized by its symmetric bell-shaped curve and central role in statistics and the natural sciences.
  • E. Procrustes
    Procrustes is a figure from Greek mythology known as a cruel bandit who mutilated travelers to force them to fit his iron bed, until he was slain by the hero Theseus.
  • F. None of above. chosen

Provenance (5 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_69a8862d562481908d7025a1c1f67c0d completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6465245c8190b1ee84628c62c529 completed March 6, 2026, 5:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0f12fd8819099759ebcdfc19494 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1e3587c8190bca329c68ff31c41 completed March 8, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69ada2977bfc8190ad028e17184fccaa completed March 8, 2026, 4:23 p.m.
Created at: March 4, 2026, 7:31 p.m.