Triple
T8795729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arena Castelão |
E209283
|
entity |
| Predicate | countryStadiumRanking |
P67849
|
FINISHED |
| Object | one of the largest stadiums in Brazil |
—
|
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: one of the largest stadiums in Brazil | Statement: [Arena Castelão, countryStadiumRanking, one of the largest stadiums in Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryStadiumRanking Context triple: [Arena Castelão, countryStadiumRanking, one of the largest stadiums in Brazil]
-
A.
footballStadiumLocation
Indicates the relationship specifying where a particular football stadium is geographically located.
-
B.
associatedWithCountryStadium
Indicates that there is an association or connection between a country and a stadium, such as location, ownership, or primary use.
-
C.
oneOfLargestStadiumsByCapacity
chosen
Indicates that a stadium is among the largest in a given set or region when ranked by seating capacity.
-
D.
UEFAStadiumCategory
Indicates the classification of a stadium according to UEFA’s official stadium category standards and requirements.
-
E.
countryCapitalStadium
Indicates that a stadium is located in and serves as a principal sports venue for the capital city of a given country.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa24ca08190a7738a7f1c446456 |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1d48f08190b325a77d4c76d223 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:44 p.m.