Triple
T26759380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Roja |
E674757
|
entity |
| Predicate | FIFAConfederationsCupBestResult |
P107923
|
FINISHED |
| Object | runners-up |
—
|
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: runners-up | Statement: [La Roja, FIFAConfederationsCupBestResult, runners-up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FIFAConfederationsCupBestResult Context triple: [La Roja, FIFAConfederationsCupBestResult, runners-up]
-
A.
FIFAConfederationsCupTitleYear
Indicates the specific year in which an entity won a FIFA Confederations Cup title.
-
B.
fifaConfederation
Indicates the regional football governing confederation with which an entity (typically a national team or association) is officially affiliated.
-
C.
FIFAClubWorldTitles
Indicates the number of FIFA Club World Cup titles a club has won.
-
D.
fifaConfederationsCupRunnerUp
chosen
Indicates that an entity finished in second place (was the runner-up) in a specified edition of the FIFA Confederations Cup.
-
E.
WorldCupWins
Indicates the number of times an entity (typically a national team) has won the FIFA World Cup tournament.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f618dafb6c8190b4f53a7fcbf967e3 |
completed | May 2, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:57 a.m.