Triple
T29636179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VQ-VAE |
E755720
|
entity |
| Predicate | codebookSize |
P140973
|
FINISHED |
| Object | hyperparameter |
—
|
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: hyperparameter | Statement: [VQ-VAE, codebookSize, hyperparameter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codebookSize Context triple: [VQ-VAE, codebookSize, hyperparameter]
-
A.
hasVocabularySize
chosen
Indicates the size or number of vocabulary items possessed or used by an entity.
-
B.
codeLengthSymbol
Indicates a relationship where a symbol is associated with, or assigned, a specific code length (such as in an encoding or compression scheme).
-
C.
characterSetSize
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
D.
hasCharacterSetSizeCategory
Indicates the relationship between something and the category that classifies the size of its character set.
-
E.
stateSizeBytes
Indicates the size of a given state or stateful data in terms of the number of bytes it occupies.
- 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_69f0ef88fbe081908f0ad90c1c413f1c |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f66e6a2790819082fb230e553bf4c5 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:44 p.m.