Triple
T32669270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AEVB |
E835244
|
entity |
| Predicate | inferenceNetworkType |
P3937
|
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: [AEVB, inferenceNetworkType, encoder network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inferenceNetworkType Context triple: [AEVB, inferenceNetworkType, encoder network]
-
A.
neuralEngineType
Indicates the specific kind or category of neural processing engine associated with or used by an entity.
-
B.
supportsInferenceOf
Indicates that one entity provides a logical basis or justification for concluding or deriving another entity.
-
C.
networkType
chosen
Indicates the category or kind of network associated with or used by an entity (e.g., wired, wireless, virtual, or specific protocol-based networks).
-
D.
inferenceAlgorithm
Indicates that one entity is an algorithm or method used to draw conclusions or derive new information from data or premises about another entity.
-
E.
hasNeuralNetwork
Indicates that an entity possesses, incorporates, or is equipped with a neural network.
- 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_69f349303ccc8190a70d0f6e8a21d3fb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c7ab10a88190bc44bfb0e61ead52 |
completed | May 3, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:08 a.m.