Triple
T29636218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neural Discrete Representation Learning |
E755721
|
entity |
| Predicate | modelComponent |
P14071
|
FINISHED |
| Object | encoder network |
—
|
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: encoder network | Statement: [Neural Discrete Representation Learning, modelComponent, encoder network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelComponent Context triple: [Neural Discrete Representation Learning, modelComponent, encoder network]
-
A.
modelIn
Indicates that one entity serves as a representation or simulation of another entity.
-
B.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
C.
componentFrom
Indicates that one entity is derived from, produced by, or originates as a component of another entity.
-
D.
component3
Indicates that one entity is the third component or sub-part within a larger composite structure or system involving another entity.
-
E.
component1
chosen
Indicates that one entity functions as a constituent or part of another entity within a larger whole.
- 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.