Triple
T36491786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | miniImageNet |
E899067
|
entity |
| Predicate | hasFewShotSetting |
P191924
|
FINISHED |
| Object | N-way K-shot classification |
—
|
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: N-way K-shot classification | Statement: [miniImageNet, hasFewShotSetting, N-way K-shot classification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFewShotSetting Context triple: [miniImageNet, hasFewShotSetting, N-way K-shot classification]
-
A.
requiresFineTuningOf
Indicates that one entity needs the adjustment, calibration, or refinement of another entity in order to function correctly or optimally.
-
B.
canBeFineTuned
Indicates that one entity (typically a model or system) is capable of being further trained or adjusted using additional data or tasks to improve or specialize its behavior.
-
C.
oneOfFew
Indicates that the subject is one member of a small, limited set of entities that share a specified property or role.
-
D.
equipmentTypeTrainedOn
Indicates the type of equipment on which an entity has received training or is qualified to operate.
-
E.
hasLimitedVocabulary
Indicates that an entity possesses or uses only a small or restricted set of words or terms in communication or expression.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69fcef636dfc819085cf91323f2e4edd |
completed | May 7, 2026, 8 p.m. |
Created at: May 3, 2026, 4:10 p.m.