Triple
T30357361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huawei P50 Pocket |
E772184
|
entity |
| Predicate | rearCameraSpectrumResolution |
P7238
|
FINISHED |
| Object | 32 MP |
—
|
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: 32 MP | Statement: [Huawei P50 Pocket, rearCameraSpectrumResolution, 32 MP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearCameraSpectrumResolution Context triple: [Huawei P50 Pocket, rearCameraSpectrumResolution, 32 MP]
-
A.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
B.
spectralResolution
chosen
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
-
C.
rearCameraMainResolution
Indicates the primary resolution (in megapixels or similar units) of a device’s main rear-facing camera.
-
D.
hasCameraResolution
Indicates that an entity is associated with a specific camera resolution value or specification.
-
E.
frontCameraResolution
Indicates the resolution quality or pixel count of a device’s front-facing (selfie) camera.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6823fe8c48190a8911627f79dd949 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 7:57 p.m.