Triple
T11194504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweden national football team |
E264885
|
entity |
| Predicate | WorldCupBestResultYear |
P24548
|
FINISHED |
| Object | 1958 |
—
|
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: 1958 | Statement: [Sweden national football team, WorldCupBestResultYear, 1958]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldCupBestResultYear Context triple: [Sweden national football team, WorldCupBestResultYear, 1958]
-
A.
WorldCupVictories
Indicates the number of times an entity has won the FIFA World Cup tournament.
-
B.
bestWorldCupResultYear
chosen
Indicates the year in which an entity achieved its best (highest) result in a World Cup tournament.
-
C.
WorldCupWins
Indicates the number of times an entity (typically a national team) has won the FIFA World Cup tournament.
-
D.
worldCupWinnerWith
Indicates that one entity is the winner of a specified FIFA World Cup tournament associated with the other entity.
-
E.
worldCupAppearanceYear
Indicates the specific year in which an entity participated in a 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8bf14e481908563b15790af4d20 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf4461c8190af84060f7db83211 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.