Triple
T17372250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | König's theorem |
E422345
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Peter König |
—
|
NE ONNED1 |
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 König | Statement: [König's theorem, namedAfter, Peter König]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter König Context triple: [König's theorem, namedAfter, Peter König]
-
A.
Peter König
chosen
Peter König is a German mathematician known for his contributions to graph theory, particularly König's theorem on bipartite graphs.
-
B.
Michael König
Michael König is a German name shared by several notable individuals, including actors, musicians, and athletes.
-
C.
Ron König
Ron König is a Dutch politician who serves as the mayor of the historic Hanseatic city of Deventer in the Netherlands.
-
D.
Markus König
Markus König is a relatively obscure individual whose specific public achievements or biographical details are not widely documented.
-
E.
Paul König
Paul König was a German naval officer best known for commanding the merchant submarine Deutschland on its pioneering transatlantic voyages during World War I.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a69d93c81908ce2d909857a3a11 |
completed | April 19, 2026, 2:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a019568a27c8190af1bbe6db75f3e6f |
in_progress | May 11, 2026, 8:38 a.m. |
Created at: April 10, 2026, 5:44 a.m.