Triple
T21046820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sperner family |
E518470
|
entity |
| Predicate | relatedConcept |
P37
|
FINISHED |
| Object | LYM inequality |
—
|
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: LYM inequality | Statement: [Sperner family, relatedConcept, LYM inequality]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LYM inequality Context triple: [Sperner family, relatedConcept, LYM inequality]
-
A.
Hardy–Littlewood–Pólya inequality
The Hardy–Littlewood–Pólya inequality is a fundamental result in majorization theory and inequalities that characterizes how convex functions behave under rearrangements of sequences or vectors.
-
B.
Brunn–Minkowski inequality
The Brunn–Minkowski inequality is a fundamental result in convex geometry and analysis that relates the volumes of sets in Euclidean space to the volume of their Minkowski sum, underpinning many isoperimetric and functional inequalities.
-
C.
Muirhead's inequality
Muirhead's inequality is a fundamental result in symmetric inequalities that compares sums of symmetric power terms of variables based on majorization of exponent sequences.
-
D.
Karamata's inequality
Karamata's inequality is a fundamental result in majorization theory that generalizes several classical inequalities by comparing sums of convex (or concave) functions over majorized sequences.
-
E.
Riesz rearrangement inequality
The Riesz rearrangement inequality is a fundamental result in mathematical analysis that provides an optimal bound for integrals of products of functions in terms of their symmetric decreasing rearrangements.
- 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: LYM inequality Target entity description: The LYM inequality is a fundamental result in extremal set theory that bounds the size of an antichain in a finite Boolean lattice by relating it to binomial coefficients.
-
A.
Hardy–Littlewood–Pólya inequality
The Hardy–Littlewood–Pólya inequality is a fundamental result in majorization theory and inequalities that characterizes how convex functions behave under rearrangements of sequences or vectors.
-
B.
Brunn–Minkowski inequality
The Brunn–Minkowski inequality is a fundamental result in convex geometry and analysis that relates the volumes of sets in Euclidean space to the volume of their Minkowski sum, underpinning many isoperimetric and functional inequalities.
-
C.
Muirhead's inequality
Muirhead's inequality is a fundamental result in symmetric inequalities that compares sums of symmetric power terms of variables based on majorization of exponent sequences.
-
D.
Karamata's inequality
Karamata's inequality is a fundamental result in majorization theory that generalizes several classical inequalities by comparing sums of convex (or concave) functions over majorized sequences.
-
E.
Riesz rearrangement inequality
The Riesz rearrangement inequality is a fundamental result in mathematical analysis that provides an optimal bound for integrals of products of functions in terms of their symmetric decreasing rearrangements.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcf4d26481908b639996500a8319 |
completed | April 21, 2026, 4:28 a.m. |
Created at: April 16, 2026, 2:34 p.m.