Triple
T21371886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilm Hosenfeld |
E527085
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hosenfeld |
—
|
NE NERFINISHED |
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: Hosenfeld | Statement: [Wilm Hosenfeld, familyName, Hosenfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hosenfeld Context triple: [Wilm Hosenfeld, familyName, Hosenfeld]
-
A.
Hosenfeld
chosen
Hosenfeld is a German surname most notably associated with Wilm Hosenfeld, a Wehrmacht officer known for helping to save Jews during World War II.
-
B.
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.
-
C.
Hauerz
Hauerz is a village and district of the spa town Bad Wurzach in the Ravensburg district of Baden-Württemberg, Germany.
-
D.
Horneff
Horneff is a German-language surname most notably borne by American actor Wil Horneff.
-
E.
Marloffstein
Marloffstein is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its rural character and proximity to the city of Erlangen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51e80808190ba5cb05667af02a9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0af44d88190aedd3b2127bb297d |
completed | April 22, 2026, 11:27 a.m. |
Created at: April 16, 2026, 5:10 p.m.