Triple
T37202085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helios |
E922063
|
entity |
| Predicate | typeOfTheaters |
—
|
GENERATED |
| Object | multiplex |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfTheaters Context triple: [Helios, typeOfTheaters, multiplex]
-
A.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
-
B.
cinemaType
chosen
Indicates the specific category or kind of cinema associated with an entity (e.g., multiplex, art house, drive-in).
-
C.
scopeOfTheatres
Indicates that there is a defined range, coverage, or extent of activities, responsibilities, or influence associated with particular theatres (e.g., theaters of operation or venues).
-
D.
featureOfTheatres
Indicates that something is a characteristic, amenity, or component that is typically found in or associated with theatres.
-
E.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
- F. None of above.
Provenance (1 batch)
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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:15 p.m.