Triple
T12597355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runge–Kutta methods |
E300766
|
entity |
| Predicate | comparedTo |
P278
|
FINISHED |
| Object | Euler method |
E54272
|
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: Euler method | Statement: [Runge–Kutta methods, comparedTo, Euler method]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Euler method Context triple: [Runge–Kutta methods, comparedTo, Euler method]
-
A.
Euler’s method for numerical integration
chosen
Euler’s method for numerical integration is a simple first-order numerical procedure used to approximate solutions to ordinary differential equations by stepping forward in small increments.
-
B.
Heun’s method
Heun’s method is a second-order Runge–Kutta numerical integration technique that improves on Euler’s method by using a predictor-corrector approach to achieve greater accuracy.
-
C.
Euler–Maruyama method
The Euler–Maruyama method is a basic time-stepping scheme for numerically approximating solutions to stochastic differential equations, widely used in simulations of systems with noise such as Langevin dynamics.
-
D.
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.
-
E.
Newton’s method
Newton’s method is an iterative numerical technique used to find successively better approximations to the roots of a real-valued function.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cf33b88190bff339fcd3142cc8 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec75fc08190aa13cbb0161eb35c |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 9, 2026, 5:08 p.m.