Triple
T34602703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O2 Forum Kentish Town |
E888509
|
entity |
| Predicate | capacityStanding |
P89353
|
FINISHED |
| Object | 2300 |
—
|
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: 2300 | Statement: [O2 Forum Kentish Town, capacityStanding, 2300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityStanding Context triple: [O2 Forum Kentish Town, capacityStanding, 2300]
-
A.
standingCapacity
chosen
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
B.
hasCapacityIncludingStanding
Indicates that an entity’s total capacity includes both seated and standing occupants.
-
C.
hasSeatingCapacityWithStanding
Indicates that an entity has a total seating capacity that explicitly includes standing room capacity as part of its overall accommodation.
-
D.
roomCapacity
Indicates the maximum number of people or occupants that a room is designed or allowed to hold.
-
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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7234bcaa48190ac970759d34e254a |
completed | May 3, 2026, 10:28 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:03 a.m.