Triple
T18724390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BERT |
E457858
|
entity |
| Predicate | fineTuningApproach |
P28297
|
FINISHED |
| Object | task-specific output layer on top of shared encoder |
—
|
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: task-specific output layer on top of shared encoder | Statement: [BERT, fineTuningApproach, task-specific output layer on top of shared encoder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fineTuningApproach Context triple: [BERT, fineTuningApproach, task-specific output layer on top of shared encoder]
-
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.
trainedNear
Indicates that one entity received training at a location that is geographically close to another specified entity or location.
-
D.
controlledApproachTo
Indicates a deliberate, regulated, or carefully managed way of proceeding toward or dealing with another entity.
-
E.
tuningMethod
chosen
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56abcfc048190a01dee959e768768 |
completed | April 19, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.