Triple
T8929340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virtual Cockpit |
E212611
|
entity |
| Predicate | screenSizeOption |
P13749
|
FINISHED |
| Object | 12.3‑inch display (typical) |
—
|
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: 12.3‑inch display (typical) | Statement: [Virtual Cockpit, screenSizeOption, 12.3‑inch display (typical)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenSizeOption Context triple: [Virtual Cockpit, screenSizeOption, 12.3‑inch display (typical)]
-
A.
availableDisplaySizes
chosen
Indicates the set of display size options that can be provided or used for a given entity.
-
B.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
C.
modelSize
Indicates the quantitative measure of how large or complex a model is, typically in terms of parameters, layers, or memory footprint.
-
D.
hasTopScreenSize
Indicates that an entity (typically a device) possesses a top screen with a specified size or dimension.
-
E.
paletteSize
Indicates the number of distinct colors included in a given color palette.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc667470308190a75ba63de803e3a2 |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.