Triple
T23142650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naive Bayes classifier |
E577500
|
entity |
| Predicate | trainingComplexity |
P28756
|
FINISHED |
| Object | linear in number of samples and features |
—
|
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: linear in number of samples and features | Statement: [Naive Bayes classifier, trainingComplexity, linear in number of samples and features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingComplexity Context triple: [Naive Bayes classifier, trainingComplexity, linear in number of samples and features]
-
A.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
B.
hasComplexity
chosen
Indicates that something possesses a certain level or type of complexity, often in terms of structure, behavior, or difficulty.
-
C.
controlsComplexityBy
Indicates that one entity manages, limits, or regulates the complexity of another entity, process, or system.
-
D.
typicalComplexity
Indicates the usual or characteristic level of complexity associated with an entity, process, or situation.
-
E.
difficulty
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
- 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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18ecb72fc8190a24e8f5756217a36 |
completed | April 29, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4 p.m.