Triple
T4293682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3C |
E99656
|
entity |
| Predicate | canUseNetworkType |
P55278
|
FINISHED |
| Object | convolutional neural networks |
—
|
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: convolutional neural networks | Statement: [A3C, canUseNetworkType, convolutional neural networks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canUseNetworkType Context triple: [A3C, canUseNetworkType, convolutional neural networks]
-
A.
networkType
Indicates the category or kind of network associated with or used by an entity (e.g., wired, wireless, virtual, or specific protocol-based networks).
-
B.
canUse
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
C.
isOnNetwork
Indicates that an entity is currently connected to, accessible through, or operating within a specified network.
-
D.
networkRequirement
Indicates that one entity requires access to or use of another entity’s network resources or connectivity to function or be fulfilled.
-
E.
supportsNetworkingModel
Indicates that one entity provides compatibility with, or implementation of, a specified networking model for another entity.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35082228081908504e3fd7c4ca1e8 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:08 p.m.