Triple
T32214243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skolemization |
E822885
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | technique in automated theorem proving |
C15969
|
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: technique in automated theorem proving Context triple: [Skolemization, instanceOf, technique in automated theorem proving]
-
A.
automated theorem proving technique
chosen
An automated theorem proving technique is a systematic, algorithmic method used by computer programs to derive logical conclusions and verify the validity of mathematical or logical statements without human intervention.
-
B.
framework in automated theorem proving
A framework in automated theorem proving is a structured environment of algorithms, data structures, and interfaces that coordinates the representation of logical formulas, the application of inference rules, and the management of proof search to automatically derive or verify theorems.
-
C.
pioneer in automated theorem proving
A pioneer in automated theorem proving is an individual who makes foundational contributions to the theory, design, or implementation of systems that enable computers to automatically generate and verify mathematical proofs.
-
D.
interactive theorem prover
An interactive theorem prover is a software system that assists users in the formalization and step-by-step verification of mathematical proofs or program properties through human-guided logical reasoning.
-
E.
theorem prover
A theorem prover is a software system or algorithm that automatically or semi-automatically checks the validity of logical statements by deriving conclusions from axioms and inference rules.
- 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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:37 a.m.