Triple
T4277246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SVC |
E97071
|
entity |
| Predicate | regularizationParameter |
P12016
|
FINISHED |
| Object | C |
—
|
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: C | Statement: [SVC, regularizationParameter, C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regularizationParameter Context triple: [SVC, regularizationParameter, C]
-
A.
regularization
Indicates the application of a constraint or penalty to a model or function to prevent overfitting and encourage simpler, more generalizable behavior.
-
B.
parameter
chosen
Indicates that one entity serves as a parameter or argument that configures, constrains, or influences the behavior or outcome of another entity or process.
-
C.
kernelType
Indicates the specific kind or category of kernel associated with or used by an entity.
-
D.
optimizationType
Indicates the specific strategy or method used to improve performance or efficiency within a given process or system.
-
E.
typicalDampingFactor
Indicates the usual or characteristic level of damping applied in a system or process, describing how strongly motion or oscillations are typically reduced.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501ef1388190b0c968b069014a59 |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.