Triple
T24515783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Euro 2016 Team of the Tournament |
E606364
|
entity |
| Predicate | goldenBootWinnerIncluded |
P156579
|
FINISHED |
| Object | Antoine Griezmann |
—
|
NE NERFINISHED |
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: Antoine Griezmann | Statement: [UEFA Euro 2016 Team of the Tournament, goldenBootWinnerIncluded, Antoine Griezmann]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: goldenBootWinnerIncluded Context triple: [UEFA Euro 2016 Team of the Tournament, goldenBootWinnerIncluded, Antoine Griezmann]
-
A.
goldenBootShared
Indicates that the Golden Boot award for top scorer in a competition was shared between two or more players rather than awarded to a single individual.
-
B.
goldenBootWinnerTeam
Indicates the team for which a player was playing when they won the Golden Boot award.
-
C.
GoldenBootAwardYear
Indicates the year in which a particular Golden Boot award was given or corresponds to.
-
D.
previousGoldenBoot
Indicates that the subject has previously won the Golden Boot award before the referenced time or event.
-
E.
isGameSpecificAward
Indicates that an award is specific to a particular game rather than being general or cross-game.
- 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_69e2c4c725148190a4e41577c5cb409c |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a9d795288190916368e3cec1f666 |
completed | April 30, 2026, 1:01 a.m. |
Created at: April 18, 2026, 2:24 a.m.