Triple
T11555392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uris Theatre |
E274005
|
entity |
| Predicate | isOneOfLargestBroadwayHouses |
P84136
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Uris Theatre, isOneOfLargestBroadwayHouses, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfLargestBroadwayHouses Context triple: [Uris Theatre, isOneOfLargestBroadwayHouses, true]
-
A.
isBroadwayHouse
Indicates that a venue functions as a Broadway theater, typically hosting official Broadway productions.
-
B.
isOneOfLargestVenuesIn
chosen
Indicates that an entity is among the largest venues located within a specified place or region.
-
C.
numberOfBroadwayPerformances
Indicates the total count of times a production or performance has been staged on Broadway.
-
D.
hasBroadwayProduction
Indicates that a work or show has been produced and staged in a Broadway theater.
-
E.
isOneOfLargestMallsIn
Indicates that a mall ranks among the largest shopping centers located within a specified area or region.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a86be308190973fea5d7db8ba9d |
completed | April 10, 2026, 5:28 a.m. |
| PD | Predicate disambiguation | batch_69d85dc3fc2c8190bed7e2111301a77c |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:37 p.m.