Triple
T14140748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aviva Centre |
E350418
|
entity |
| Predicate | mainCourtCapacity |
P103582
|
FINISHED |
| Object | approximately 12000 |
—
|
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: approximately 12000 | Statement: [Aviva Centre, mainCourtCapacity, approximately 12000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCourtCapacity Context triple: [Aviva Centre, mainCourtCapacity, approximately 12000]
-
A.
courtyardCapacity
Indicates the maximum number of entities that can be accommodated in a courtyard at the same time.
-
B.
venueCapacityApproximate
chosen
Indicates an approximate or estimated capacity of a venue in terms of how many people it can accommodate.
-
C.
mainHallCapacity
Indicates the maximum number of people that the main hall can accommodate at one time.
-
D.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
E.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de611ed3508190add37baa30d1d134 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:47 a.m.