Triple
T36048248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schwarz-Weiß Essen |
E1042732
|
entity |
| Predicate | DFB-PokalTitleYear |
P184510
|
FINISHED |
| Object | 1959 |
—
|
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: 1959 | Statement: [Schwarz-Weiß Essen, DFB-PokalTitleYear, 1959]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: DFB-PokalTitleYear Context triple: [Schwarz-Weiß Essen, DFB-PokalTitleYear, 1959]
-
A.
numberOfGermanSupercups
Indicates the total count of German Supercup titles associated with a given team or entity.
-
B.
EuropeanChampionYear
Indicates the year in which an entity achieved the status of European champion in a given competition or discipline.
-
C.
numberOfGermanChampionships
Indicates the count of German championship titles associated with a given entity.
-
D.
numberOfDFBPokalTitles
Indicates the number of DFB-Pokal titles that an entity has won.
-
E.
numberOfGermanFootballerOfTheYearAwards
Indicates the number of times an entity has received the German Footballer of the Year award.
- 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_69f76e2e41f8819091f9fb0536920fec |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b35e32d481909ef0220e6f6ff4a8 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2c66054819083897e25edb65ba7 |
completed | May 3, 2026, 8:40 p.m. |
Created at: May 3, 2026, 4:07 p.m.