Triple
T3469414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Cup final 1975 |
E73216
|
entity |
| Predicate | Bayern MunichTitleCount |
P15090
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [European Cup final 1975, Bayern MunichTitleCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Bayern MunichTitleCount Context triple: [European Cup final 1975, Bayern MunichTitleCount, 2]
-
A.
numberOfTitlesOfMostSuccessfulClub
Indicates the total count of titles won by the club that has achieved the highest number of titles among all clubs in the given context.
-
B.
UEFAChampionsLeagueTitles
chosen
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
C.
numberOfGermanChampionships
Indicates the count of German championship titles associated with a given entity.
-
D.
CopaDelReyTitles
Indicates the number of Copa del Rey championship titles an entity has won.
-
E.
EuropeanChampionshipTitles
Indicates the number of European Championship titles an entity has won.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb376d288190abac85f2ffa853dc |
completed | March 8, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.