Triple
T11657761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Series 90 |
E277051
|
entity |
| Predicate | supportsCameraApplication |
P85677
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Series 90, supportsCameraApplication, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCameraApplication Context triple: [Series 90, supportsCameraApplication, true]
-
A.
usesCameraApp
chosen
Indicates that an entity operates or interacts with a camera application to capture photos, record videos, or manage camera-related functions.
-
B.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
C.
supportsCameraControl
Indicates that one entity provides functionality for another entity to remotely manage or adjust camera settings or operations.
-
D.
usesCameraType
Indicates that one entity employs or operates a specific type or category of camera.
-
E.
supportsARFilters
Indicates that one entity provides or enables augmented reality (AR) filter functionality for another entity or within a given context.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d0331481909682b2e504e4c9a0 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.