Triple
T9306697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Blackburn Hospital |
E223902
|
entity |
| Predicate | hasOperatingTheatres |
P87984
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
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: hasOperatingTheatres Context triple: [Royal Blackburn Hospital, hasOperatingTheatres, yes]
-
A.
operatedTheatersIn
Indicates that an entity managed or ran the day-to-day operations of one or more theaters in a specified location or context.
-
B.
hasNumberOfCinemas
Indicates the quantity of cinemas associated with a given entity.
-
C.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
-
D.
hasAuditorium
Indicates that one entity possesses or includes an auditorium as part of its facilities.
-
E.
hasTheatreDistrictRole
Indicates that an entity holds a specific role, function, or designation within a theatre district.
- F. None of above. chosen
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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:36 p.m.