Triple
T10454359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Circle-Vision 360° theater |
E246512
|
entity |
| Predicate | screenArrangement |
P46737
|
FINISHED |
| Object | circular |
—
|
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: circular | Statement: [Circle-Vision 360° theater, screenArrangement, circular]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenArrangement Context triple: [Circle-Vision 360° theater, screenArrangement, circular]
-
A.
arrangementType
chosen
Indicates the specific kind or category of arrangement that characterizes how the related entities are organized or structured in relation to each other.
-
B.
screensAt
Indicates that one entity shows, projects, or displays another entity (such as a film, program, or content) on a screen or at a screening venue.
-
C.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
-
D.
displayConfiguration
Indicates a relationship where one entity defines or presents the arrangement, layout, or settings used to visually display another entity.
-
E.
arrangement
Indicates a relationship where entities are organized, ordered, or positioned in a particular configuration or sequence relative to one another.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe47fee48190b38ec0466ff0165a |
completed | April 7, 2026, 12:53 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:17 p.m.