Triple
T21303664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Zerbe |
E525133
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Zerbe |
E869372
|
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: Zerbe | Statement: [Karl Zerbe, familyName, Zerbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zerbe Context triple: [Karl Zerbe, familyName, Zerbe]
-
A.
Zerbe
chosen
Zerbe is a surname of German origin borne by various notable individuals, including American actor Anthony Zerbe.
-
B.
Eisele
Eisele is a surname most notably associated with Donn F. Eisele, an American astronaut who flew on the Apollo 7 mission.
-
C.
Fahrenkopf
Fahrenkopf is a surname most prominently associated with Frank J. Fahrenkopf Jr., an American lawyer, lobbyist, and former chairman of the Republican National Committee.
-
D.
Nitzschka
Nitzschka is a village and district of the town of Wurzen in the Free State of Saxony, Germany.
-
E.
Gotschlich
Gotschlich is the surname of Emil C. Gotschlich, an American physician and microbiologist known for his pioneering work on meningococcal vaccines.
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385da340819083c07f353f2142b0 |
completed | April 21, 2026, 8:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a099ed32130819081479d9845d74ac3 |
completed | May 17, 2026, 10:56 a.m. |
Created at: April 16, 2026, 4:05 p.m.