Triple
T8483196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WaveGlow |
E200567
|
entity |
| Predicate | probabilityModel |
P12745
|
FINISHED |
| Object | exact likelihood model |
—
|
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: exact likelihood model | Statement: [WaveGlow, probabilityModel, exact likelihood model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: probabilityModel Context triple: [WaveGlow, probabilityModel, exact likelihood model]
-
A.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
B.
definesProbability
chosen
Indicates that one entity specifies or assigns the probability value associated with another entity or event.
-
C.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
D.
riskModel
Indicates a relationship where an entity serves as or is associated with a model used to assess, quantify, or manage risk for another entity or situation.
-
E.
performanceModel
Indicates a relationship where one entity serves as a performance model that represents, predicts, or characterizes the performance behavior of another entity.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53845e881909eeb32863c7aa942 |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:12 p.m.