Triple
T24633593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gavi |
E609743
|
entity |
| Predicate | dateAwardedKopaTrophy |
P156849
|
FINISHED |
| Object | 2022 |
—
|
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: 2022 | Statement: [Gavi, dateAwardedKopaTrophy, 2022]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateAwardedKopaTrophy Context triple: [Gavi, dateAwardedKopaTrophy, 2022]
-
A.
FIFAPuskásAward
Indicates that an entity has received or is associated with the FIFA Puskás Award, recognizing the scorer of the most aesthetically significant or beautiful goal in a given year.
-
B.
FIFAWorldCupYashinAwardYear
Indicates the year in which a specific instance of the FIFA World Cup Yashin Award was given.
-
C.
BallonDorYear
Indicates the specific year in which a Ballon d'Or award was given.
-
D.
FIFAWorldCupGoldenBallYear
Indicates the year in which a given FIFA World Cup Golden Ball award was received.
-
E.
FIFABallonDorWinner
Indicates that the subject is the football player who won the FIFA Ballon d'Or award in the specified year or context.
- F. None of above. chosen
Provenance (4 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_69e2c4d28f848190ac38c400060e943d |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:32 a.m.