Triple
T23121214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayern Munich basketball |
E576897
|
entity |
| Predicate | numberOfGermanSupercups |
P150989
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Bayern Munich basketball, numberOfGermanSupercups, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGermanSupercups Context triple: [Bayern Munich basketball, numberOfGermanSupercups, 3]
-
A.
numberOfGermanChampionships
Indicates the count of German championship titles associated with a given entity.
-
B.
numberOfBundesligaTitles
Indicates the quantity of Bundesliga championship titles that an entity has won.
-
C.
wonBundesligaWith
Indicates that one entity achieved victory in the Bundesliga while being associated with (e.g., playing for or coaching) the other entity.
-
D.
numberOfGermanFootballerOfTheYearAwards
Indicates the number of times an entity has received the German Footballer of the Year award.
-
E.
clubGermanChampionship
Indicates that a club has won the German football championship.
- 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_69e245f6c2e881909a228fdcfeb7c7d3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e50c500819095d59aef44388153 |
completed | April 29, 2026, 4:51 a.m. |
| PD | Predicate disambiguation | batch_69ef89f020588190b43393e048e7eda3 |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:59 p.m.