Triple
T22006306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbourne |
E543456
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Ryan O’Keeffe |
—
|
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: Ryan O’Keeffe | Statement: [Airbourne, hasPart, Ryan O’Keeffe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryan O’Keeffe Context triple: [Airbourne, hasPart, Ryan O’Keeffe]
-
A.
Ryan O’Keeffe
chosen
Ryan O’Keeffe is the drummer for the Australian hard rock band Airbourne, known for their high-energy, AC/DC-inspired sound.
-
B.
Aidan O'Herlihy
Aidan O'Herlihy is a member of the O'Herlihy family, known in part through his relation to Irish-born television and film director Michael O'Herlihy.
-
C.
Matthew O’Callaghan
Matthew O’Callaghan is an American animator, director, and writer known for his work on Disney films and various animated projects, including contributions to The Great Mouse Detective.
-
D.
Tim O'Kelly
Tim O'Kelly is an American actor best known for his role as the young police officer in Peter Bogdanovich's 1968 film "Targets."
-
E.
Dion O’Leary
Dion O’Leary is the central protagonist of the 1937 historical drama film "In Old Chicago," which dramatizes events leading up to the Great Chicago Fire of 1871.
- 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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a0afa881908318a4ebe211ca28 |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:21 p.m.