Triple
T28322989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Champions League 2019–20 |
E717327
|
entity |
| Predicate | winnerTitleCountForBayern |
P102199
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [UEFA Champions League 2019–20, winnerTitleCountForBayern, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerTitleCountForBayern Context triple: [UEFA Champions League 2019–20, winnerTitleCountForBayern, 6]
-
A.
bayernTitleCount
chosen
Indicates the number of titles that Bayern Munich has won.
-
B.
clubNumberOfEuropeanCupsWonWithBayern
Indicates the number of European Cups/Champions League titles a club has won specifically while playing as Bayern Munich.
-
C.
numberOfBundesligaTitles
Indicates the quantity of Bundesliga championship titles that an entity has won.
-
D.
goalsForBayernMunich
Indicates the number of goals that were scored in favor of Bayern Munich in a given match or context.
-
E.
BayernMunichEuropeanCupFinalAppearanceNumber
Indicates the number of times Bayern Munich has appeared in a European Cup final.
- 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 28, 2026, 12:26 a.m.