Triple
T11631735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl Zuckmayer Medal |
E276413
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object | Daniel Kehlmann |
E783282
|
NE 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: Daniel Kehlmann | Statement: [Carl Zuckmayer Medal, notableRecipient, Daniel Kehlmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Kehlmann Context triple: [Carl Zuckmayer Medal, notableRecipient, Daniel Kehlmann]
-
A.
Daniel Kehlmann
chosen
Daniel Kehlmann is a contemporary German-language novelist best known internationally for his bestselling historical novel "Measuring the World."
-
B.
Tobias Moers
Tobias Moers is a German automotive executive best known for leading Mercedes-AMG before becoming CEO of luxury sports car maker Aston Martin Lagonda.
-
C.
Lorenz Bock
Lorenz Bock was a German politician who became the inaugural Minister-President of the post–World War II state of Württemberg-Hohenzollern.
-
D.
Ursula Thiess
Ursula Thiess was a German-born film actress and model who appeared in European and Hollywood productions in the mid-20th century.
-
E.
Johann Heermann
Johann Heermann was a notable early 17th-century German Lutheran hymn writer and poet whose texts were widely used in Protestant church music.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25aa9188190ab13d79139f37e7e |
completed | April 10, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee87a20af481909b47775c7cb6ec3b |
completed | April 26, 2026, 9:46 p.m. |
Created at: April 8, 2026, 9:39 p.m.