Triple
T18205227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HuBERT |
E435884
|
entity |
| Predicate | pretrainingStage |
P130224
|
FINISHED |
| Object | offline clustering of acoustic 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: offline clustering of acoustic features | Statement: [HuBERT, pretrainingStage, offline clustering of acoustic features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pretrainingStage Context triple: [HuBERT, pretrainingStage, offline clustering of acoustic features]
-
A.
pretrainingRole
Indicates the role or function an entity serves specifically during a pretraining phase or process.
-
B.
initialStage
Indicates that one entity represents the first or starting phase in a sequence, process, or development of another entity.
-
C.
earlyTraining
Indicates that an entity receives or provides training at an early stage relative to a process, development period, or typical timeline.
-
D.
trainingModel
Indicates that an entity is engaged in the process of teaching, adjusting, or optimizing a model using data or experience.
-
E.
encodingStage
Indicates the specific phase or step within an encoding process at which a given action, transformation, or state occurs.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.