Triple
T19431590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stade du Hainaut |
E486125
|
entity |
| Predicate | hasSeatingCapacityForFootball |
P2491
|
FINISHED |
| Object | about 25000 |
—
|
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: about 25000 | Statement: [Stade du Hainaut, hasSeatingCapacityForFootball, about 25000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingCapacityForFootball Context triple: [Stade du Hainaut, hasSeatingCapacityForFootball, about 25000]
-
A.
seatingCapacity
chosen
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
playerCapacity
Indicates the maximum number of players that can simultaneously participate in or be accommodated by something (such as a game, session, or venue).
-
C.
capacityForWorldCup
Indicates the maximum number of spectators a venue can accommodate specifically for World Cup events.
-
D.
venueCapacityApproximate
Indicates an approximate or estimated capacity of a venue in terms of how many people it can accommodate.
-
E.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6335b4e388190913ded15ad165b7b |
completed | April 20, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.