Triple
T10803126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LSU Tigers |
E254893
|
entity |
| Predicate | footballStadiumCapacity |
P3507
|
FINISHED |
| Object | over 100000 |
—
|
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 100000 | Statement: [LSU Tigers, footballStadiumCapacity, over 100000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: footballStadiumCapacity Context triple: [LSU Tigers, footballStadiumCapacity, over 100000]
-
A.
footballStadiumLocation
Indicates the relationship specifying where a particular football stadium is geographically located.
-
B.
homeStadiumCapacity
chosen
Indicates the seating capacity of the stadium that serves as a team's or organization's home venue.
-
C.
stadiumCapacityContext
Indicates the seating capacity of a stadium as it applies within a specific contextual scope (such as time, event, or configuration).
-
D.
stadiumCapacityApprox
Indicates an approximate number of people that a stadium can accommodate.
-
E.
oneOfLargestStadiumsByCapacity
Indicates that a stadium is among the largest in a given set or region when ranked by seating capacity.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7336feff88190b638b7d62d34da0e |
completed | April 9, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:18 p.m.