Triple
T37404080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dell G3 |
E929074
|
entity |
| Predicate | typicalResolutionOption |
P5732
|
FINISHED |
| Object | 1920x1080 |
—
|
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: 1920x1080 | Statement: [Dell G3, typicalResolutionOption, 1920x1080]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalResolutionOption Context triple: [Dell G3, typicalResolutionOption, 1920x1080]
-
A.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
B.
typicalInputResolution
Indicates the usual or standard resolution at which input is expected or typically processed.
-
C.
displayResolution
chosen
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
D.
targetResolution
Indicates the specific resolution or level of detail that an action, process, or system is intended to achieve or operate at.
-
E.
supportsDisplayResolution
Indicates that one entity is capable of operating with, rendering, or otherwise accommodating the specified display resolution of 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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.