Triple
T38698074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadcom BCM2763 |
E950058
|
entity |
| Predicate | supportsCameraResolution |
P103408
|
FINISHED |
| Object | 20 megapixels |
—
|
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: 20 megapixels | Statement: [Broadcom BCM2763, supportsCameraResolution, 20 megapixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCameraResolution Context triple: [Broadcom BCM2763, supportsCameraResolution, 20 megapixels]
-
A.
hasCameraResolution
chosen
Indicates that an entity is associated with a specific camera resolution value or specification.
-
B.
supportsDisplayResolution
Indicates that one entity is capable of operating with, rendering, or otherwise accommodating the specified display resolution of another entity.
-
C.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
D.
telephotoCameraResolution
Indicates the image resolution capability of a device’s telephoto camera in a given context.
-
E.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:33 p.m.