Triple
T4432934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notre Dame Stadium |
E95376
|
entity |
| Predicate | expandedSeatingCapacity |
P9426
|
FINISHED |
| Object | 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: 80000+ | Statement: [Notre Dame Stadium, expandedSeatingCapacity, 80000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expandedSeatingCapacity Context triple: [Notre Dame Stadium, expandedSeatingCapacity, 80000+]
-
A.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
typicalSeatingCapacityUpperBound
Indicates the maximum number of seats that a venue or vehicle is typically designed or allowed to accommodate under normal conditions.
-
C.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
D.
expandedCapacity
chosen
Indicates that an entity’s capacity has been increased beyond its previous or standard level.
-
E.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3556cd83881908547aa311c4f17fa |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f6078cc8190831b89f404198cc5 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:31 p.m.