Triple
T5253470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nintendo 3DS |
E118641
|
entity |
| Predicate | hasBottomScreenResolution |
P5732
|
FINISHED |
| Object | 320×240 pixels |
—
|
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: 320×240 pixels | Statement: [Nintendo 3DS, hasBottomScreenResolution, 320×240 pixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBottomScreenResolution Context triple: [Nintendo 3DS, hasBottomScreenResolution, 320×240 pixels]
-
A.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
B.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
-
C.
displayResolution
chosen
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
D.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
E.
supportsHandheldMode
Indicates that an entity is capable of operating or being used in a handheld mode.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ba1cca88190bebd516851b9bf7f |
completed | March 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69bd77c30bac8190a883ca45da35d667 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:50 p.m.