Triple
T17815656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Ferris |
E444831
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Karl Ferris |
—
|
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: Karl Ferris | Statement: [Karl Ferris, name, Karl Ferris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karl Ferris Context triple: [Karl Ferris, name, Karl Ferris]
-
A.
Karl Ferris
chosen
Karl Ferris is a British photographer best known for his pioneering psychedelic imagery on 1960s rock album covers, particularly for Jimi Hendrix.
-
B.
Karl Burns
Karl Burns was an English drummer best known for his multiple stints with the influential post-punk band The Fall, where his inventive and sometimes volatile presence became part of the group’s legend.
-
C.
Karl VanDevender
Karl VanDevender is an American physician best known as the husband of acclaimed novelist Ann Patchett.
-
D.
Bob Ferris
Bob Ferris is the central, working-class everyman character from the British television sitcoms "The Likely Lads" and "Whatever Happened to the Likely Lads?".
-
E.
Karl Dane
Karl Dane was a Danish-American silent film actor best known for his comic roles in 1920s Hollywood, particularly as part of the popular screen duo "Dane & Arthur."
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887f7d048190b6d813b9f0fab3e7 |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 10, 2026, 10:14 a.m.