Triple
T23301586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | residual maker matrix |
E590316
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object | ANOVA decomposition |
—
|
NE NERFINISHED |
How this triple was built (3 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: ANOVA decomposition | Statement: [residual maker matrix, appearsIn, ANOVA decomposition]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ANOVA decomposition Context triple: [residual maker matrix, appearsIn, ANOVA decomposition]
-
A.
Fitting decomposition
Fitting decomposition is a fundamental theorem in group theory that expresses a finite group as a product of its largest nilpotent normal subgroup and a complementary subgroup, playing a key role in the structural analysis of groups.
-
B.
KAN decomposition
KAN decomposition is a factorization of a semisimple Lie group into the product of a maximal compact subgroup, a maximal abelian subgroup, and a nilpotent subgroup, fundamental in Lie theory and harmonic analysis.
-
C.
Decomposition
Decomposition is a short story from David Benioff’s collection "When the Nines Roll Over," exploring themes of decay, change, and the unraveling of personal or artistic integrity.
-
D.
MANOVA
MANOVA (Multivariate Analysis of Variance) is a statistical technique that tests for differences in multiple dependent variables across groups simultaneously by analyzing their combined variance–covariance structure.
-
E.
Satterthwaite's theorem
Satterthwaite's theorem is a foundational result in social choice theory that characterizes the limitations of fair and non-manipulable voting systems, closely associated with the Gibbard–Satterthwaite theorem.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ANOVA decomposition Target entity description: ANOVA decomposition is a statistical technique that partitions the total variability in data into components attributable to different sources or factors, enabling the analysis of their individual and joint effects.
-
A.
Fitting decomposition
Fitting decomposition is a fundamental theorem in group theory that expresses a finite group as a product of its largest nilpotent normal subgroup and a complementary subgroup, playing a key role in the structural analysis of groups.
-
B.
KAN decomposition
KAN decomposition is a factorization of a semisimple Lie group into the product of a maximal compact subgroup, a maximal abelian subgroup, and a nilpotent subgroup, fundamental in Lie theory and harmonic analysis.
-
C.
Decomposition
Decomposition is a short story from David Benioff’s collection "When the Nines Roll Over," exploring themes of decay, change, and the unraveling of personal or artistic integrity.
-
D.
MANOVA
MANOVA (Multivariate Analysis of Variance) is a statistical technique that tests for differences in multiple dependent variables across groups simultaneously by analyzing their combined variance–covariance structure.
-
E.
Satterthwaite's theorem
Satterthwaite's theorem is a foundational result in social choice theory that characterizes the limitations of fair and non-manipulable voting systems, closely associated with the Gibbard–Satterthwaite theorem.
- F. None of above. chosen
Provenance (2 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d37fd08190ad2d199c54324c02 |
completed | April 29, 2026, 5:27 a.m. |
Created at: April 17, 2026, 5:04 p.m.