Triple
T5139290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York theatre community |
E115904
|
entity |
| Predicate | typicalVenueTypes |
P10640
|
FINISHED |
| Object | proscenium theatres |
—
|
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: proscenium theatres | Statement: [New York theatre community, typicalVenueTypes, proscenium theatres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVenueTypes Context triple: [New York theatre community, typicalVenueTypes, proscenium theatres]
-
A.
typicalVenues
Indicates that the specified locations are common or standard places where the associated activity, event, or entity usually occurs or is hosted.
-
B.
refersToVenueType
chosen
Indicates that one entity specifies or identifies the type or category of venue associated with another entity.
-
C.
primaryVenues
Indicates the main or most important venues associated with or used by a given entity.
-
D.
typicalVenueMetroArea
Indicates the metropolitan area where an entity is most commonly or characteristically located or hosted.
-
E.
venueConcept
Indicates a relationship where a venue is associated with, characterized by, or defined in terms of a particular concept or thematic idea.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.