Triple
T146117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SyNAPSE neuromorphic computing program |
E3333
|
entity |
| Predicate | applicationArea |
P1129
|
FINISHED |
| Object | autonomous systems |
—
|
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: autonomous systems | Statement: [SyNAPSE neuromorphic computing program, applicationArea, autonomous systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicationArea Context triple: [SyNAPSE neuromorphic computing program, applicationArea, autonomous systems]
-
A.
appliesTo
chosen
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
B.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
C.
appliesAcross
Indicates that a condition, rule, or property holds uniformly over multiple items, cases, or contexts.
-
D.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
E.
appliedBy
Indicates that an action, process, or treatment is carried out or executed by a particular agent or 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ea7eac8190884a53453a9e0dd6 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.