Triple
T24313958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gale’s example in stable matching with couples |
E612751
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | example in stable matching theory |
C48683
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: example in stable matching theory Context triple: [Gale’s example in stable matching with couples, instanceOf, example in stable matching theory]
-
A.
result in social choice theory
A result in social choice theory is a formal theorem or proposition that characterizes how individual preferences can be aggregated into a collective decision under specified axioms or conditions.
-
B.
pairing
Pairing is the conceptual class representing the association or coupling of two complementary or related entities treated as a single combined unit.
-
C.
object in optimal stopping theory
An object in optimal stopping theory is an abstract entity (such as a stochastic process, payoff function, or stopping rule) whose evolution or evaluation over time determines when it is best to stop observing and take an action to maximize expected reward or minimize expected cost.
-
D.
bargaining solution concept
A bargaining solution concept is a formal rule or principle that specifies how two or more parties should divide the benefits of cooperation given their feasible payoffs and disagreement outcomes.
-
E.
matchmaker
A matchmaker is an entity that identifies, evaluates, and connects compatible parties—such as individuals, groups, or systems—to form mutually beneficial relationships based on defined criteria.
- F. None of above. chosen
Provenance (1 batch)
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_69e2d7da491c8190b6e6218af50923db |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 18, 2026, 1:45 a.m.