Triple
T2608869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sauer |
E58726
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Joachim Sauer |
E8441
|
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: Joachim Sauer | Statement: [Sauer, hasNotableBearer, Joachim Sauer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joachim Sauer Context triple: [Sauer, hasNotableBearer, Joachim Sauer]
-
A.
Joachim Sauer
chosen
Joachim Sauer is a German quantum chemist and professor known both for his research in theoretical chemistry and for being married to former Chancellor Angela Merkel.
-
B.
Monte Hellman
Monte Hellman was an American film director and producer best known for his influential low-budget cult classics, including the road movie "Two-Lane Blacktop."
-
C.
Oskar Kummetz
Oskar Kummetz was a German Kriegsmarine admiral during World War II who commanded naval forces in several key operations, including the invasion of Norway.
-
D.
Randal Kleiser
Randal Kleiser is an American film director best known for directing the hit musical "Grease" (1978) and other popular films of the late 20th century.
-
E.
Stephan Jost
Stephan Jost is a Canadian art museum director best known for leading the Art Gallery of Ontario in Toronto.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd868acc481909444c99a621cdbec |
completed | March 7, 2026, 7:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83e1efb88190b79c2c6ac0e87647 |
completed | March 10, 2026, 2:37 a.m. |
Created at: March 6, 2026, 9:49 p.m.