Triple
T17576481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feldman |
E428082
|
entity |
| Predicate | variantOf |
P4680
|
FINISHED |
| Object | Feldmann |
—
|
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: Feldmann | Statement: [Feldman, variantOf, Feldmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feldmann Context triple: [Feldman, variantOf, Feldmann]
-
A.
Feldman
chosen
Feldman is a surname of Germanic and Ashkenazi Jewish origin borne by various notable individuals across fields such as music, academia, and the arts.
-
B.
Faehlmann
Faehlmann is a surname most notably associated with Friedrich Robert Faehlmann, a prominent 19th-century Estonian writer, physician, and folklorist.
-
C.
Hosenfeld
Hosenfeld is a German surname most notably associated with Wilm Hosenfeld, a Wehrmacht officer known for helping to save Jews during World War II.
-
D.
Freimann
Freimann is a district in the northern part of Munich, Germany, known for its mix of residential areas, industrial sites, and major sports and event facilities.
-
E.
Edelmann
Edelmann is a surname of German origin borne by various individuals across fields such as music, sports, and academia.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463ca76848190a7beb6deb4b0f1a4 |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 10, 2026, 5:50 a.m.