Triple
T20660263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byrne |
E507741
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Michael 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: Michael Byrne | Statement: [Byrne, hasNotableBearer, Michael Byrne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Byrne Context triple: [Byrne, hasNotableBearer, Michael Byrne]
-
A.
Michael Byrne
chosen
Michael Byrne is a British character actor known for his numerous film and television roles, often portraying military officers or authority figures.
-
B.
Michael Boddy
Michael Boddy is a music producer best known for his work on the project Dylanesque.
-
C.
Brian Byrne
Brian Byrne is an Irish composer best known for his film scores and orchestral works, including the acclaimed music for the film "Albert Nobbs."
-
D.
Sean Byrne
Sean Byrne is an Australian filmmaker best known for directing the cult horror films "The Loved Ones" and "The Devil’s Candy."
-
E.
Michael O’Rourke
Michael O’Rourke is an Irish media entrepreneur best known as a co-founder of the international sports television network Setanta Sports.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f16adc8190b2b9a69586fa7444 |
completed | April 20, 2026, 11:12 p.m. |
Created at: April 16, 2026, 11:44 a.m.