Triple
T24286154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KNN |
E605673
|
entity |
| Predicate | parameterSelectionMethod |
P28297
|
FINISHED |
| Object | cross-validation for choosing k |
—
|
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: cross-validation for choosing k | Statement: [KNN, parameterSelectionMethod, cross-validation for choosing k]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parameterSelectionMethod Context triple: [KNN, parameterSelectionMethod, cross-validation for choosing k]
-
A.
selectionMetric
Indicates the criterion or measure used to evaluate and choose among alternative options or candidates.
-
B.
tuningMethod
chosen
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
-
C.
topicSelectionMethod
Indicates the method or criteria used to choose or determine a particular topic from among possible options.
-
D.
delegateSelectionMethod
Indicates the method or process by which responsibility or authority is assigned from one entity to another.
-
E.
questionSelectionMethod
Indicates how questions are chosen or determined from a set of possible questions.
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f56cdc08190a1e06f67dffd4769 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.