Triple
T26966490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turing reducibility |
E679186
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computability-theoretic notion |
C17828
|
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: computability-theoretic notion Context triple: [Turing reducibility, instanceOf, computability-theoretic notion]
-
A.
model of computation
A model of computation is an abstract mathematical framework that defines how algorithms are represented and executed, specifying the rules, operations, and resources available for performing computations.
-
B.
set-theoretic concept
A set-theoretic concept is an abstract mathematical idea defined in terms of sets and their elements, relationships, and operations, such as membership, union, intersection, and power sets.
-
C.
complexity measure
chosen
A complexity measure is a quantitative function or criterion used to assess and compare the intricacy, difficulty, or resource requirements of objects, systems, or problems.
-
D.
foundational principle in theoretical computer science
A foundational principle in theoretical computer science is a core, abstract concept or rule—such as computability, complexity, or formal language theory—that underlies and unifies the study of algorithms, computation models, and their inherent limits.
-
E.
theoretical computer science blog
A theoretical computer science blog is an online platform that explores and explains abstract computational concepts, models, and proofs, often connecting cutting-edge research with clear, insightful commentary for students, researchers, and enthusiasts.
- 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 27, 2026, 6:36 a.m.