Triple
T20298205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutti Frutti |
E505407
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | John Byrne |
—
|
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: John Byrne | Statement: [Tutti Frutti, writer, John Byrne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Byrne Context triple: [Tutti Frutti, writer, John Byrne]
-
A.
John Byrne
John Byrne is a renowned comic book writer and artist best known for his influential work on titles like X-Men, Fantastic Four, and Superman.
-
B.
John Byrne
chosen
John Byrne is a Scottish artist and playwright known for his distinctive visual style and acclaimed works for stage and television, including "The Slab Boys" trilogy.
-
C.
Peter Byrne
Peter Byrne was a British actor best known for his long-running role as Andy Crawford in the classic television police series "Dixon of Dock Green."
-
D.
Michael Byrne
Michael Byrne is a British character actor known for his numerous film and television roles, often portraying military officers or authority figures.
-
E.
Larry Byrne
Larry Byrne is the husband of American politician Leslie L. Byrne, who served as a U.S. Representative from Virginia.
- 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770a2cec8190912d6b0dbabc78bc |
completed | April 20, 2026, 6:57 p.m. |
Created at: April 16, 2026, 11:16 a.m.