Triple
T12295820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ultra Panavision 70 |
E293083
|
entity |
| Predicate | anamorphicSqueezeFactor |
P104317
|
FINISHED |
| Object | 1.25x |
—
|
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: 1.25x | Statement: [Ultra Panavision 70, anamorphicSqueezeFactor, 1.25x]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: anamorphicSqueezeFactor Context triple: [Ultra Panavision 70, anamorphicSqueezeFactor, 1.25x]
-
A.
aspectRatio
Indicates the proportional relationship between an entity’s width and its height.
-
B.
lensCompressionFactor
Indicates the degree to which a lens alters perceived depth and distance relationships in an image compared to real-world geometry.
-
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.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
E.
hasFocalRatio
Indicates a relationship where an optical system is associated with a specific focal ratio (f-number) that characterizes its light-gathering speed and image brightness.
- F. None of above. chosen
Provenance (4 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec02c008190a56aae60a3d9eff6 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:52 p.m.