Triple
T6833248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Successive Over-Relaxation |
E157387
|
entity |
| Predicate | optimalParameterRange |
P28992
|
FINISHED |
| Object | 1 < ω < 2 for over-relaxation |
—
|
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: 1 < ω < 2 for over-relaxation | Statement: [Successive Over-Relaxation, optimalParameterRange, 1 < ω < 2 for over-relaxation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optimalParameterRange Context triple: [Successive Over-Relaxation, optimalParameterRange, 1 < ω < 2 for over-relaxation]
-
A.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
B.
typeOfOptimality
Indicates that one entity specifies the particular notion or criterion of optimality that characterizes another entity’s optimal status or solution.
-
C.
optimizationType
Indicates the specific strategy or method used to improve performance or efficiency within a given process or system.
-
D.
controlRange
Indicates the spatial or contextual extent within which an entity can exert control or influence over another entity or process.
-
E.
rangeOf
chosen
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
- F. None of above.
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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62b1e8c8190a81d91191a54b073 |
completed | March 27, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69c6d09d95f0819091ca7f897dc21efe |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:18 p.m.