Triple
T4277197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LogisticRegression |
E97070
|
entity |
| Predicate | requiresFeatureScaling |
P55158
|
FINISHED |
| Object | often beneficial |
—
|
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: often beneficial | Statement: [LogisticRegression, requiresFeatureScaling, often beneficial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiresFeatureScaling Context triple: [LogisticRegression, requiresFeatureScaling, often beneficial]
-
A.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
B.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
C.
isFeatureBased
Indicates that one entity is derived from, determined by, or constructed using the characteristics or attributes of another entity.
-
D.
hasScaleFactorForm
Indicates that one entity is represented as a scaled version or proportional form of another, typically via a specific scale factor.
-
E.
requiresMeasures
Indicates that one entity necessitates the implementation or presence of specific measures, actions, or safeguards in relation to another entity or situation.
- 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.