Triple
T6073591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazil national football team |
E135343
|
entity |
| Predicate | numberOfFIFAConfederationsCupTitles |
P13988
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Brazil national football team, numberOfFIFAConfederationsCupTitles, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFIFAConfederationsCupTitles Context triple: [Brazil national football team, numberOfFIFAConfederationsCupTitles, 4]
-
A.
ConfederationsCupTitles
chosen
Indicates the number of FIFA Confederations Cup championships an entity has won.
-
B.
FIFAConfederationsCupTitleYear
Indicates the specific year in which an entity won a FIFA Confederations Cup title.
-
C.
FIFAU20WorldCupTitles
Indicates the number of FIFA U-20 World Cup championship titles an entity has won.
-
D.
WorldCupWins
Indicates the number of times an entity (typically a national team) has won the FIFA World Cup tournament.
-
E.
numberOfFIFAConfederations
Indicates the total count of FIFA confederations associated with a given 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_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575b9bc08190a78b3082b9ccf00c |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:11 p.m.