Triple
T6637723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France women’s national football team |
E150499
|
entity |
| Predicate | bestFifaWorldCupResultYear |
P24548
|
FINISHED |
| Object | 2011 |
—
|
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: 2011 | Statement: [France women’s national football team, bestFifaWorldCupResultYear, 2011]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestFifaWorldCupResultYear Context triple: [France women’s national football team, bestFifaWorldCupResultYear, 2011]
-
A.
bestWorldCupResultYear
chosen
Indicates the year in which an entity achieved its best (highest) result in a World Cup tournament.
-
B.
FIFABallonDorWinner
Indicates that the subject is the football player who won the FIFA Ballon d'Or award in the specified year or context.
-
C.
fifaWorldPlayerOfTheYear
Indicates that one entity has been awarded the FIFA World Player of the Year title for a given year or period.
-
D.
FIFAConfederationsCupTitleYear
Indicates the specific year in which an entity won a FIFA Confederations Cup title.
-
E.
FIFAU20WorldCupTitleYear
Indicates the year in which an entity won the FIFA U-20 World Cup title.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.