Triple
T30773977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huawei P50 Pro |
E783607
|
entity |
| Predicate | monochromeCameraResolution |
P170111
|
FINISHED |
| Object | 40 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: 40 MP | Statement: [Huawei P50 Pro, monochromeCameraResolution, 40 MP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monochromeCameraResolution Context triple: [Huawei P50 Pro, monochromeCameraResolution, 40 MP]
-
A.
hasCameraResolution
Indicates that an entity is associated with a specific camera resolution value or specification.
-
B.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
C.
frontCameraResolution
Indicates the resolution quality or pixel count of a device’s front-facing (selfie) camera.
-
D.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
-
E.
telephotoCameraResolution
Indicates the image resolution capability of a device’s telephoto camera in a given context.
- 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_69f224b1519081908b9db003fd2073e0 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68fc421dc8190862169489455a035 |
completed | May 2, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68848ad348190a2fb6e841dcfdb7d |
completed | May 2, 2026, 11:27 p.m. |
Created at: April 29, 2026, 8:40 p.m.