Triple
T14572597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gisiro Maruyama |
E341955
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Maruyama method for numerical solution of stochastic differential equations |
E31546
|
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: Maruyama method for numerical solution of stochastic differential equations | Statement: [Gisiro Maruyama, knownFor, Maruyama method for numerical solution of stochastic differential equations]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maruyama method for numerical solution of stochastic differential equations Context triple: [Gisiro Maruyama, knownFor, Maruyama method for numerical solution of stochastic differential equations]
-
A.
Euler–Maruyama method
chosen
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.
-
B.
Milstein method
The Milstein method is a numerical scheme for solving stochastic differential equations that improves on the Euler–Maruyama method by including derivative terms of the diffusion coefficient for higher accuracy.
-
C.
Itô–Stratonovich conversion formula
The Itô–Stratonovich conversion formula is a key result in stochastic calculus that provides the explicit relationship for transforming stochastic integrals between the Itô and Stratonovich interpretations.
-
D.
Euler’s method for numerical integration
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.
-
E.
Feynman–Kac formula
The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f33b1c8190bb447788bfd28d51 |
completed | April 14, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aca591081908db149ec517a999b |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:24 a.m.