Triple
T7202855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2013 UEFA Champions League Final |
E148589
|
entity |
| Predicate | BayernTitleCountAfterMatch |
P13593
|
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: [2013 UEFA Champions League Final, BayernTitleCountAfterMatch, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: BayernTitleCountAfterMatch Context triple: [2013 UEFA Champions League Final, BayernTitleCountAfterMatch, 5]
-
A.
numberOfGermanChampionships
Indicates the count of German championship titles associated with a given entity.
-
B.
numberOfTropheeDesChampionsTitles
Indicates the number of Trophée des Champions titles that an entity has won.
-
C.
numberOfCoupeDeLaLigueTitles
Indicates the total count of Coupe de la Ligue titles that an entity has won.
-
D.
homeTeamTitleCountAfterMatch
chosen
Indicates the total number of titles the home team has accumulated after the completion of the referenced match.
-
E.
CopaDelReyTitles
Indicates the number of Copa del Rey 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e94a9ee4819086de79fcdfa1836a |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.