Triple
T11893401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neo Química Arena |
E282974
|
entity |
| Predicate | capacityForWorldCup |
P102103
|
FINISHED |
| Object | approximately 68000 |
—
|
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: approximately 68000 | Statement: [Neo Química Arena, capacityForWorldCup, approximately 68000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityForWorldCup Context triple: [Neo Química Arena, capacityForWorldCup, approximately 68000]
-
A.
capacityInternationalMatches
Indicates the maximum number of international matches that can be held or accommodated.
-
B.
WorldCupSemiFinalAppearances
Indicates the number of times an entity has reached the semi-final stage of a FIFA World Cup tournament.
-
C.
capacityDuringOlympics
Indicates the seating or usage capacity of a venue, facility, or service specifically during the Olympic Games period.
-
D.
WorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup final tournaments.
-
E.
capacityRankInWorld
Indicates the relative position or ranking of an entity’s capacity compared to all similar entities worldwide.
- F. None of above. chosen
Provenance (4 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1172988190a2c13d37220f2f93 |
completed | April 10, 2026, 11:20 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.