Triple
T1462628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euler–Maruyama method |
E31546
|
entity |
| Predicate | isExplicit |
P28823
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Euler–Maruyama method, isExplicit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isExplicit Context triple: [Euler–Maruyama method, isExplicit, true]
-
A.
isSelective
Indicates that the relationship or action involves choosing or affecting only certain specific entities or options while excluding others based on particular criteria.
-
B.
exposes
Indicates making something visible, known, or vulnerable by removing cover, concealment, or protection.
-
C.
isIntense
Indicates that something exhibits a high degree of strength, force, or concentration in its quality, effect, or activity.
-
D.
exposed
Indicates that one entity has been made visible, revealed, or left unprotected to another entity or to some external influence.
-
E.
exposureType
Indicates the specific manner or context in which one entity is exposed to another entity, condition, or influence.
- F. None of above. chosen
Provenance (4 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5b6e36c81909c47b2f7e66f17d7 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c55508948190922aee3230a4323e |
completed | March 1, 2026, 11:01 p.m. |
Created at: March 1, 2026, 8 p.m.