Triple
T22116374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bram Fischer |
E546554
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fischer |
—
|
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: Fischer | Statement: [Bram Fischer, familyName, Fischer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fischer Context triple: [Bram Fischer, familyName, Fischer]
-
A.
Fischer
chosen
Fischer is a common German surname borne by numerous notable individuals across fields such as politics, science, sports, and the arts.
-
B.
Fischer
Fischer is a French beer brand known for its traditional Alsatian brewing heritage and distinctive lagers.
-
C.
Fischer Scherz
Fischer Scherz is a German publishing imprint of S. Fischer Verlag, known for its popular fiction and crime literature titles.
-
D.
Fiser
Fiser is a surname variant of Fischer, commonly associated with Central or Eastern European origins.
-
E.
Fritz
Fritz is a comedic monster character from the animated series "Monsters at Work," known for his role as the enthusiastic and quirky supervisor of the MIFT maintenance team at Monsters, Inc.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1294dc1148190b95ff00f475a6713 |
completed | April 28, 2026, 9:40 p.m. |
Created at: April 16, 2026, 8:31 p.m.