Triple
T15035933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyssa |
E378476
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Johnny Byrne |
E1105396
|
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: Johnny Byrne | Statement: [Nyssa, createdBy, Johnny Byrne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johnny Byrne Context triple: [Nyssa, createdBy, Johnny Byrne]
-
A.
Johnny Byrne
chosen
Johnny Byrne was a British television writer best known for his work on series such as Doctor Who and All Creatures Great and Small.
-
B.
John Ronane
John Ronane was a British actor known for his work in film, television, and theatre, including a role in the drama "Elizabeth R."
-
C.
Jonathan Kerrigan
Jonathan Kerrigan is a British actor known for his roles in television dramas such as Casualty, Heartbeat, and In the Club.
-
D.
Jack Doolan
Jack Doolan is a British actor best known for his role in the coming-of-age comedy-drama film "Cemetery Junction" and various appearances in UK television series.
-
E.
Michael Byrne
Michael Byrne is a British character actor known for his numerous film and television roles, often portraying military officers or authority figures.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82b29948190acda49cbec3f927a |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9ddfc13481909333690016650410 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:59 a.m.