Triple
T23142633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naive Bayes classifier |
E577500
|
entity |
| Predicate | typicalFeatureModel |
P104084
|
FINISHED |
| Object | Gaussian distribution for continuous 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: Gaussian distribution for continuous features | Statement: [Naive Bayes classifier, typicalFeatureModel, Gaussian distribution for continuous features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFeatureModel Context triple: [Naive Bayes classifier, typicalFeatureModel, Gaussian distribution for continuous features]
-
A.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
B.
featuresModel
chosen
Indicates that one entity includes, exposes, or is characterized by a particular model as one of its defining components or capabilities.
-
C.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
D.
entityCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular characteristic or attribute.
-
E.
targetFeature
Indicates that one entity is the specific feature, attribute, or characteristic that another entity is directed toward, focused on, or intended to affect.
- 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.