Triple
T17906287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aron City |
E447709
|
entity |
| Predicate | notableResident |
P1092
|
FINISHED |
| Object | Bunny Bravo |
—
|
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: Bunny Bravo | Statement: [Aron City, notableResident, Bunny Bravo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bunny Bravo Context triple: [Aron City, notableResident, Bunny Bravo]
-
A.
Bunny Bravo
chosen
Bunny Bravo is Johnny Bravo’s caring and long-suffering mother in the animated television series "Johnny Bravo."
-
B.
Bunny
Bunny is a small village and civil parish in Nottinghamshire, England, known for its historic church and rural character.
-
C.
Bunny
"Bunny" is a 2005 Telugu-language romantic action film starring Allu Arjun, known for its energetic performances, catchy music, and mass appeal.
-
D.
Bunny
Bunny is a supporting character in the psychological thriller film "Don't Worry Darling," portrayed as a seemingly content housewife whose role becomes more complex as the story’s unsettling reality is revealed.
-
E.
Bunny
Bunny is a given name that can be used as a nickname or first name for people, often conveying a playful or affectionate character.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49e9c7f54819088c6d2ce7bbea073 |
completed | April 19, 2026, 9:21 a.m. |
Created at: April 10, 2026, 10:19 a.m.