Triple
T8349142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fisher |
E196115
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Fischer |
E81650
|
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: Fischer | Statement: [Fisher, hasVariant, Fischer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fischer Context triple: [Fisher, hasVariant, Fischer]
-
A.
Fischer
Fischer is a French beer brand known for its traditional Alsatian brewing heritage and distinctive lagers.
-
B.
Fischer
chosen
Fischer is a common German surname borne by numerous notable individuals across fields such as politics, science, sports, and the arts.
-
C.
Fiser
Fiser is a surname variant of Fischer, commonly associated with Central or Eastern European origins.
-
D.
Fritz
Fritz is an individual known primarily as the offspring of Fifi.
-
E.
Fritz
Fritz is the hunchbacked assistant to Dr. Frankenstein in the 1931 horror film "Frankenstein," known for helping to procure the monster’s body parts and brain.
- 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_69ca82edd63c8190b876b8465464c5fa |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8016c4188190a5ff93078e74dc39 |
completed | March 31, 2026, 8:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc74e11f881908b52d0ffea751c96 |
completed | April 2, 2026, 1:33 a.m. |
Created at: March 30, 2026, 5:58 p.m.