Triple
T15304163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dubai Government Workshop |
E365854
|
entity |
| Predicate | assetTypeMaintained |
P118034
|
FINISHED |
| Object | light vehicles |
—
|
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: light vehicles | Statement: [Dubai Government Workshop, assetTypeMaintained, light vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assetTypeMaintained Context triple: [Dubai Government Workshop, assetTypeMaintained, light vehicles]
-
A.
assetType
Indicates the specific category or classification of an asset within a broader asset framework or system.
-
B.
assetOwnerType
Indicates the type or category of entity that owns or holds the asset.
-
C.
ownsAssetType
Indicates that an entity possesses ownership rights over an asset of a specified type.
-
D.
hasMaintenanceType
Indicates the specific category or kind of maintenance associated with an asset, component, or maintenance event.
-
E.
asset
Indicates that one entity is a valuable resource, item, or property owned, controlled, or beneficially used by 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ccef14c819099c5ebe962e7f867 |
completed | April 16, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:15 a.m.