Triple
T1005830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CinemaScope |
E21708
|
entity |
| Predicate | imageAspectRatio |
P1991
|
FINISHED |
| Object | 2.35:1 |
—
|
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: 2.35:1 | Statement: [CinemaScope, imageAspectRatio, 2.35:1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageAspectRatio Context triple: [CinemaScope, imageAspectRatio, 2.35:1]
-
A.
aspectRatio
chosen
Indicates the proportional relationship between an entity’s width and its height.
-
B.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
C.
pegRatio
Indicates the relationship between a company’s price-to-earnings (P/E) ratio and its expected earnings growth rate, expressing how highly the market values each unit of anticipated growth.
-
D.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
E.
isProportionalTo
Indicates that one quantity varies in constant ratio to another, so when one changes, the other changes by a fixed multiplicative factor.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51303548190a5ee3c0797fc3245 |
completed | March 1, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b2e7108190b338b6c19d4aff55 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.