Triple
T30590211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gazprom Arena |
E778633
|
entity |
| Predicate | capacityMaximum |
P14460
|
FINISHED |
| Object | over 80000 |
—
|
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: over 80000 | Statement: [Gazprom Arena, capacityMaximum, over 80000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityMaximum Context triple: [Gazprom Arena, capacityMaximum, over 80000]
-
A.
capacityCategory
Indicates the classification of something based on the amount or volume it can hold, handle, or accommodate.
-
B.
maximumCapacity
chosen
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
C.
unitCapacity
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
D.
capacityRecord
Indicates a recorded measure of how much of a resource, space, or system is available or can be utilized at a given time.
-
E.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
- 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_69f224a1570c8190a85d3ac330479a79 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68979b8308190b4a5a8bc3d2282a6 |
completed | May 2, 2026, 11:32 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:24 p.m.