Triple
T4277000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GridSearchCV |
E97067
|
entity |
| Predicate | definedInModule |
P23699
|
FINISHED |
| Object | sklearn.model_selection |
—
|
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: sklearn.model_selection | Statement: [GridSearchCV, definedInModule, sklearn.model_selection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definedInModule Context triple: [GridSearchCV, definedInModule, sklearn.model_selection]
-
A.
areDefinedIn
chosen
Indicates that the referenced entities are specified, described, or formally established within a particular source, context, or scope.
-
B.
definedVia
Indicates that one entity is specified, characterized, or given its meaning by reference to another entity or construct.
-
C.
alsoDefinedInPackage
Indicates that the same element or concept is additionally defined or declared in another software package.
-
D.
previouslyDefinedIn
Indicates that something has been defined or introduced earlier in time or in a prior context relative to the current reference point.
-
E.
hasModuleConstruct
Indicates that an entity includes, defines, or is composed of a specific module as one of its structural or functional components.
- 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.