Triple
T23178670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parken Stadium |
E579085
|
entity |
| Predicate | hasSeatingCapacityRange |
P96445
|
FINISHED |
| Object | 35000–40000 for football |
—
|
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: 35000–40000 for football | Statement: [Parken Stadium, hasSeatingCapacityRange, 35000–40000 for football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingCapacityRange Context triple: [Parken Stadium, hasSeatingCapacityRange, 35000–40000 for football]
-
A.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
hasSeatingCapacityCategory
chosen
Indicates the classification of an entity based on the range or category of how many people it can seat.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
hasSeatingCapacityWithStanding
Indicates that an entity has a total seating capacity that explicitly includes standing room capacity as part of its overall accommodation.
-
E.
typicalSeatingCapacityLowerBound
Indicates the minimum number of seats that an entity is typically designed or expected to provide.
- 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_69e245fd2a388190b814c0dfa15f7148 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f6cbe5481909444479b7eac47f7 |
completed | April 29, 2026, 4:56 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:04 p.m.