Triple
T6256690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jürgen |
E140183
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Jürgen Prochnow |
E122693
|
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: Jürgen Prochnow | Statement: [Jürgen, hasNotableBearer, Jürgen Prochnow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jürgen Prochnow Context triple: [Jürgen, hasNotableBearer, Jürgen Prochnow]
-
A.
Jürgen Prochnow
chosen
Jürgen Prochnow is a German actor best known internationally for his intense performances in films such as "Das Boot" and numerous Hollywood productions.
-
B.
Jürgen Büscher
Jürgen Büscher is a screenwriter best known for co-writing the 1993 German war film "Stalingrad."
-
C.
Eckhard Pfeiffer
Eckhard Pfeiffer is a German-American businessman best known for serving as CEO of Compaq Computer Corporation during its rapid expansion in the 1990s.
-
D.
Rainer Klausmann
Rainer Klausmann is a Swiss cinematographer known for his work on acclaimed European films, including the World War II drama "Downfall."
-
E.
Jochen Kuttler
Jochen Kuttler is a German local politician who serves as the mayor of the town of Wadern in Saarland.
- 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_69c008c95c5c819084bd3dd56133d84d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063653910819095f1dc3b90ce77db |
completed | March 22, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7421871888190aab99c6c5f6c147d |
completed | March 28, 2026, 2:51 a.m. |
Created at: March 22, 2026, 4:24 p.m.