Triple
T690953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theatre Row |
E13389
|
entity |
| Predicate | audienceCapacityType |
P16993
|
FINISHED |
| Object | small to mid-size theaters |
—
|
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: small to mid-size theaters | Statement: [Theatre Row, audienceCapacityType, small to mid-size theaters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceCapacityType Context triple: [Theatre Row, audienceCapacityType, small to mid-size theaters]
-
A.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
-
C.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
D.
hasAudienceReception
Indicates the relationship between a work or event and how it is received, perceived, or evaluated by its audience.
-
E.
audienceSizeApproximate
Indicates an estimated or approximate number of people in the audience for an event or content.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0aebde88190a49d421477713103 |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d221d38819083c0adda81f59b07 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49dc0e6a08190b81d82a6f2571c41 |
completed | March 1, 2026, 8:12 p.m. |
Created at: March 1, 2026, 7:36 p.m.