Triple
T18942037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merriweather Post Pavilion |
E463405
|
entity |
| Predicate | hasPavilionCapacityApprox |
P103582
|
FINISHED |
| Object | 9000 |
—
|
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: 9000 | Statement: [Merriweather Post Pavilion, hasPavilionCapacityApprox, 9000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPavilionCapacityApprox Context triple: [Merriweather Post Pavilion, hasPavilionCapacityApprox, 9000]
-
A.
hasPavilion
Indicates that one entity possesses, includes, or is associated with a pavilion as part of its structure, property, or facilities.
-
B.
hasPavilionFunction
Indicates that something serves the role or function of a pavilion, such as providing a designated space or facility for specific activities or purposes.
-
C.
venueCapacityApproximate
chosen
Indicates an approximate or estimated capacity of a venue in terms of how many people it can accommodate.
-
D.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
E.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3ec857081908da0f974604f2c65 |
completed | April 20, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69e4a2efec5c8190840704016bf547a1 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 11:59 a.m.