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.