Triple
T2584033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minskoff Theatre |
E57156
|
entity |
| Predicate | isBroadwayHouse |
P40516
|
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: [Minskoff Theatre, isBroadwayHouse, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBroadwayHouse Context triple: [Minskoff Theatre, isBroadwayHouse, true]
-
A.
numberOfBroadwayPerformances
Indicates the total count of times a production or performance has been staged on Broadway.
-
B.
broadwayTransfer
Indicates a transfer or move of a theatrical production or performance to a Broadway venue or run.
-
C.
hasBroadwayTitle
Indicates that an entity is associated with a specific title used for its Broadway production or representation.
-
D.
originalBroadwayStar
Indicates that the subject was a member of the original Broadway cast in the specified role or production.
-
E.
broadwayRunStatus
Indicates the status of a production’s run on Broadway, such as whether it is upcoming, currently running, or has closed.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3cb33a08190a3eae1a95e1b63bf |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd37ef248819090ab6b86b67e355f |
completed | March 7, 2026, 7:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.