Triple
T20062405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Bonner |
E499511
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | 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: Bonner | Statement: [Tony Bonner, familyName, Bonner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bonner Context triple: [Tony Bonner, familyName, Bonner]
-
A.
Bonner
Bonner is a residential suburb in the Gungahlin district of Canberra, Australian Capital Territory.
-
B.
Bonner
chosen
Bonner is a surname shared by various notable individuals across fields such as politics, sports, and the arts.
-
C.
Bonderman
Bonderman is a surname most prominently associated with American billionaire investor and private equity pioneer David Bonderman.
-
D.
Boerne
Boerne is a small, historic town in south-central Texas known for its German heritage, charming downtown, and scenic Hill Country surroundings.
-
E.
Conerly
Conerly is a surname most notably associated with Charlie Conerly, a prominent mid-20th-century American football quarterback.
- 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.