Triple

T3600026
Position Surface form Disambiguated ID Type / Status
Subject John W. Tukey E76231 entity
Predicate developedConcept P73 FINISHED
Object 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.
E371261 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: Tukey's honestly significant difference test | Statement: [John W. Tukey, developedConcept, Tukey's honestly significant difference test]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tukey's honestly significant difference test
Context triple: [John W. Tukey, developedConcept, Tukey's honestly significant difference test]
  • A. 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.
  • B. 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.
  • C. 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.
  • 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. Mauchly
    Mauchly is the surname of John W. Mauchly, the American physicist and co-inventor of the ENIAC, one of the earliest general-purpose electronic digital computers.
  • 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: Tukey's honestly significant difference test
Triple: [John W. Tukey, developedConcept, Tukey's honestly significant difference test]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tukey's honestly significant difference test
Target entity description: 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.
  • A. 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.
  • B. 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.
  • C. 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.
  • 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. Mauchly
    Mauchly is the surname of John W. Mauchly, the American physicist and co-inventor of the ENIAC, one of the earliest general-purpose electronic digital computers.
  • 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_69ad85d93dcc819094fba90cf70f4996 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc19fd57481908ce5c9daf168e213 completed March 8, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4031a41d08190b8e87c452601a625 completed March 13, 2026, 12:29 p.m.
NEDg Description generation batch_69b406fd33e08190a6f06eddec8516e9 completed March 13, 2026, 12:45 p.m.
NED2 Entity disambiguation (via description) batch_69b408778220819086935bfa9c0dd4fd completed March 13, 2026, 12:52 p.m.
Created at: March 8, 2026, 3:22 p.m.