Triple
T23448188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Die DFB-Frauen |
E565598
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object | Nadine Angerer |
—
|
NE NERFINISHED |
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: Nadine Angerer | Statement: [Die DFB-Frauen, notablePlayer, Nadine Angerer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nadine Angerer Context triple: [Die DFB-Frauen, notablePlayer, Nadine Angerer]
-
A.
Nadine Angerer
chosen
Nadine Angerer is a retired German goalkeeper widely regarded as one of the greatest in women's soccer history, known for her World Cup–winning performances and multiple international awards.
-
B.
Daniela Gresch
Daniela Gresch is a television creator and writer best known for co-creating the German Netflix drama series "High Seas."
-
C.
Tanja Spengler
Tanja Spengler is known as the former wife of German rock musician Peter Maffay.
-
D.
Martina Gedeck
Martina Gedeck is a German actress acclaimed for her versatile performances in film and television, including prominent roles in internationally recognized dramas.
-
E.
Sabine Michalek
Sabine Michalek is a German local politician who serves as the mayor of the town of Einbeck in Lower Saxony.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64b27988190b4722425da964407 |
completed | April 29, 2026, 6:33 a.m. |
Created at: April 17, 2026, 5:52 p.m.