Triple
T15537811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraguay national football team |
E370394
|
entity |
| Predicate | bestFIFAWorldCupResultYear |
P24548
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [Paraguay national football team, bestFIFAWorldCupResultYear, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestFIFAWorldCupResultYear Context triple: [Paraguay national football team, bestFIFAWorldCupResultYear, 2010]
-
A.
bestWorldCupResultYear
chosen
Indicates the year in which an entity achieved its best (highest) result in a World Cup tournament.
-
B.
bestResultFifaU17WWCYear
Indicates the year in which an entity achieved its best performance or result at the FIFA U-17 Women's World Cup.
-
C.
bestWorldCupFinish
Indicates the highest stage or ranking a team or participant has ever achieved in any edition of the World Cup.
-
D.
FIFABallonDorWinner
Indicates that the subject is the football player who won the FIFA Ballon d'Or award in the specified year or context.
-
E.
bestConfederationsCupResultYear
Indicates the year in which an entity achieved its best (highest) result in the FIFA Confederations Cup.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442f3c688190a599165e526af2ed |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:06 a.m.