Triple
T20003567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WKInterfaceImage |
E494393
|
entity |
| Predicate | canLoadImageFrom |
P127767
|
FINISHED |
| Object | asset catalog |
—
|
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: asset catalog | Statement: [WKInterfaceImage, canLoadImageFrom, asset catalog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canLoadImageFrom Context triple: [WKInterfaceImage, canLoadImageFrom, asset catalog]
-
A.
canBeLoadedBy
chosen
Indicates that one entity is capable of being loaded, initialized, or brought into use by another entity.
-
B.
canBeLoadedAt
Indicates that an entity is capable of being placed onto or into another entity (such as a vehicle, container, or system) at a specific location or point in time.
-
C.
containsImage
Indicates that one entity includes or embeds an image as part of its content or structure.
-
D.
usesImageModel
Indicates that one entity employs or relies on an image-based model (such as a computer vision or image generation model) in relation to another entity or task.
-
E.
hasImageryFrom
Indicates that one entity contains, incorporates, or is derived from the imagery produced or provided by 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a3ad148190918f9dce755fe470 |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:33 p.m.