Triple
T20062403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Bonner |
E499511
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tony Bonner |
—
|
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: Tony Bonner | Statement: [Tony Bonner, name, Tony Bonner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Bonner Context triple: [Tony Bonner, name, Tony Bonner]
-
A.
Tony Bonner
chosen
Tony Bonner is an Australian actor best known for his roles in film and television during the 1960s and 1970s, including the series "Skippy the Bush Kangaroo."
-
B.
Anthony Bonner
Anthony Bonner is a translator best known for his English translations of literary works, including those of Jorge Luis Borges.
-
C.
Pat Bunch
Pat Bunch was an American country music songwriter known for penning numerous hits for major artists throughout the 1980s and 1990s.
-
D.
Rick Bonner
Rick Bonner is a recurring character on the TV sitcom "The Facts of Life," known primarily as a romantic partner of Jo Polniaczek.
-
E.
Tom W. Bonner
Tom W. Bonner was an American nuclear physicist renowned for his pioneering experimental work in neutron physics and nuclear instrumentation.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66376f2d4819081b9e1b265650e5b |
completed | April 20, 2026, 5:33 p.m. |
Created at: April 11, 2026, 3:39 p.m.