Triple
T28193049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Euro 2012 Golden Boot |
E716368
|
entity |
| Predicate | matchesPlayedByWinner |
P165128
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [UEFA Euro 2012 Golden Boot, matchesPlayedByWinner, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchesPlayedByWinner Context triple: [UEFA Euro 2012 Golden Boot, matchesPlayedByWinner, 5]
-
A.
matchesPlayedIn
Indicates that a particular match was played in a specified location, event, or competition context.
-
B.
matchesPlayedAs
Indicates that a certain number of matches were played with a specific role, configuration, or context.
-
C.
totalMatchesPlayed
Indicates the total number of matches that have been played by the referenced entity or between the related entities.
-
D.
qualificationMatchesPlayed
Indicates that the number of qualification matches associated with an entity has been played or completed.
-
E.
gamesWonBy
Indicates the number of games that have been won by a particular entity in a given 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 27, 2026, 10:26 p.m.