Triple
T14101942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klara Kohl |
E339402
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Peter Kohl |
E68442
|
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: Peter Kohl | Statement: [Klara Kohl, hasChild, Peter Kohl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Kohl Context triple: [Klara Kohl, hasChild, Peter Kohl]
-
A.
Peter Kohl
chosen
Peter Kohl is a German businessman and author best known as the son of former German Chancellor Helmut Kohl.
-
B.
Daniel Günther
Daniel Günther is a German politician from the Christian Democratic Union (CDU) who serves as the Minister-President of the northern federal state of Schleswig-Holstein.
-
C.
Georg Scholz
Georg Scholz was a German painter associated with the New Objectivity movement, known for his socially critical, realist depictions of Weimar-era society.
-
D.
Wolfgang Vogel
Wolfgang Vogel was a prominent East German lawyer best known for brokering high-profile prisoner exchanges and political deals between East and West Germany during the Cold War.
-
E.
Christian Scholz
Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbbf0b08190ba1ea3657d6db005 |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7de2af88190b9ed8cfeece74e50 |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:22 p.m.