Chayes–McKellar–Winn theorem
E1568557
UNEXPLORED
The Chayes–McKellar–Winn theorem is a result in mathematical physics and statistical mechanics that provides rigorous conditions for phase transitions in certain probabilistic or lattice-based models.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Chayes–McKellar–Winn theorem canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T23052618 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chayes–McKellar–Winn theorem Context triple: [Danica McKellar, coAuthorOf, Chayes–McKellar–Winn theorem]
-
A.
Szekeres–Lindström theorem
The Szekeres–Lindström theorem is a result in combinatorics that characterizes the maximum size of intersecting families of subsets, serving as a precursor to and special case of the Erdős–Ko–Rado theorem.
-
B.
Hales–Jewett theorem
The Hales–Jewett theorem is a fundamental result in Ramsey theory that guarantees the existence of large monochromatic combinatorial lines in high-dimensional grids under any finite coloring.
-
C.
Kesten’s theorem
Kesten’s theorem is a fundamental result in probability theory that characterizes when a random walk on a group is transient or recurrent, with deep implications for random walks on groups and percolation theory.
-
D.
Lieb–Mattis theorem
The Lieb–Mattis theorem is a result in quantum many-body physics that characterizes the ordering and total spin of energy levels in certain antiferromagnetic spin systems.
-
E.
Hammersley–Clifford theorem
The Hammersley–Clifford theorem is a fundamental result in probability theory and statistics that links Markov random fields with Gibbs distributions by showing that, under positivity conditions, the Markov property is equivalent to factorization over cliques of an underlying graph.
- 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: Chayes–McKellar–Winn theorem Target entity description: The Chayes–McKellar–Winn theorem is a result in mathematical physics and statistical mechanics that provides rigorous conditions for phase transitions in certain probabilistic or lattice-based models.
-
A.
Szekeres–Lindström theorem
The Szekeres–Lindström theorem is a result in combinatorics that characterizes the maximum size of intersecting families of subsets, serving as a precursor to and special case of the Erdős–Ko–Rado theorem.
-
B.
Hales–Jewett theorem
The Hales–Jewett theorem is a fundamental result in Ramsey theory that guarantees the existence of large monochromatic combinatorial lines in high-dimensional grids under any finite coloring.
-
C.
Kesten’s theorem
Kesten’s theorem is a fundamental result in probability theory that characterizes when a random walk on a group is transient or recurrent, with deep implications for random walks on groups and percolation theory.
-
D.
Lieb–Mattis theorem
The Lieb–Mattis theorem is a result in quantum many-body physics that characterizes the ordering and total spin of energy levels in certain antiferromagnetic spin systems.
-
E.
Hammersley–Clifford theorem
The Hammersley–Clifford theorem is a fundamental result in probability theory and statistics that links Markov random fields with Gibbs distributions by showing that, under positivity conditions, the Markov property is equivalent to factorization over cliques of an underlying graph.
- F. None of above. chosen
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.