Triple
T23791167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | System F |
E588093
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | polymorphically typed lambda calculus |
C26025
|
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: polymorphically typed lambda calculus Context triple: [System F, instanceOf, polymorphically typed lambda calculus]
-
A.
polymorphic type system
chosen
A polymorphic type system is a type system that allows functions, data structures, or expressions to be written generically so they can operate uniformly on values of multiple (often unspecified or parameterized) types.
-
B.
representation in lambda calculus
A representation in lambda calculus is a systematic encoding of data, operations, or computational structures solely using lambda terms, enabling them to be manipulated and reasoned about within the formalism.
-
C.
dependently typed programming language
A dependently typed programming language is one in which types can depend on values, enabling the expression and static verification of rich logical properties directly in the type system.
-
D.
gradually typed programming language
A gradually typed programming language is one that allows both static and dynamic typing in the same codebase, enabling developers to optionally add or refine type annotations over time.
-
E.
functional programming language
A functional programming language is a programming paradigm where computation is treated as the evaluation of mathematical functions, emphasizing immutability, first-class functions, and avoidance of side effects.
- F. None of above.
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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
Created at: April 17, 2026, 7:17 p.m.