Triple
T17040824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Crank |
E413441
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Crank–Nicolson method |
E87777
|
NE FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Crank–Nicolson method | Statement: [John Crank, knownFor, Crank–Nicolson method]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Crank–Nicolson method Context triple: [John Crank, knownFor, Crank–Nicolson method]
-
A.
Crank–Nicolson scheme
chosen
The Crank–Nicolson scheme is a finite difference method for numerically solving time-dependent partial differential equations, especially parabolic ones like the heat equation, known for its second-order accuracy and unconditional stability.
-
B.
Lax–Wendroff method
The Lax–Wendroff method is a numerical scheme for solving hyperbolic partial differential equations that achieves second-order accuracy in both space and time by using a Taylor series expansion and flux approximations.
-
C.
Runge–Kutta methods
Runge–Kutta methods are a family of iterative techniques for numerically solving ordinary differential equations with higher accuracy than simple one-step schemes.
-
D.
Lax–Friedrichs scheme
The Lax–Friedrichs scheme is a numerical method for approximating solutions to hyperbolic partial differential equations, known for its simplicity and strong stability properties.
-
E.
theta-method
The theta-method is a family of numerical time-stepping schemes for solving ordinary and partial differential equations that unifies explicit, implicit, and Crank–Nicolson methods through a single weighting parameter.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f6a0c08190a838279b83b55b72 |
completed | April 18, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012338a95c8190951db96209edb61a |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.