Triple
T4277192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LogisticRegression |
E97070
|
entity |
| Predicate | regularizationControlledBy |
P55154
|
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: [LogisticRegression, regularizationControlledBy, C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regularizationControlledBy Context triple: [LogisticRegression, regularizationControlledBy, 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.
rangeControlledBy
Indicates that the extent or scope of something is regulated, limited, or determined by another entity.
-
C.
controlled
Indicates that one entity has power, authority, or influence to direct, regulate, or determine the behavior, actions, or state of another entity.
-
D.
regulatesIn
Indicates that one entity controls, modulates, or influences the activity, expression, or behavior of another entity within a system or process.
-
E.
trainControl
Indicates that one entity exercises authority over or manages the operation, direction, or behavior of another entity in a training or instructional context.
- 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_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. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:07 p.m.