Triple
T3712029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonny River |
E81437
|
entity |
| Predicate | nearTown |
P2064
|
FINISHED |
| Object | Bonny |
E291344
|
NE FINISHED |
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: Bonny | Statement: [Bonny River, nearTown, Bonny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bonny Context triple: [Bonny River, nearTown, Bonny]
-
A.
Bonny
chosen
Bonny is a historic coastal town and important oil and gas hub located on Bonny Island in Nigeria’s Rivers State.
-
B.
Bonny Billy
Bonny Billy is an alias of American singer-songwriter and actor Will Oldham, known for his introspective, genre-blurring indie folk music.
-
C.
Betsy
Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
-
D.
Betsy
Betsy is a common diminutive or nickname for the given name Elizabeth.
-
E.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc58617bc8190bb712d1c90394215 |
completed | March 8, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4ce0834288190b16cf49477dc2ed9 |
completed | March 14, 2026, 2:55 a.m. |
Created at: March 8, 2026, 3:33 p.m.