Triple
T20108461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonavista—Burin—Trinity |
E490259
|
entity |
| Predicate | hasCensusSubdivision |
P138716
|
FINISHED |
| Object | Burin |
—
|
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: Burin | Statement: [Bonavista—Burin—Trinity, hasCensusSubdivision, Burin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burin Context triple: [Bonavista—Burin—Trinity, hasCensusSubdivision, Burin]
-
A.
Burin
chosen
Burin is a small coastal town on the Burin Peninsula in Newfoundland and Labrador, Canada, historically known for its fishing industry and maritime heritage.
-
B.
Burin
Burin is a Palestinian village located in the Nablus Governorate in the northern West Bank.
-
C.
Whetstone
Whetstone is a suburban area in north London known for its residential character and local high street, forming part of the London Borough of Barnet.
-
D.
Banryū
Banryū was a Japanese warship that served in the late Edo period and took part in the Boshin War’s Naval Battle of Hakodate.
-
E.
Kalthof
Kalthof is a district of the city of Iserlohn in North Rhine-Westphalia, Germany.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666ddb09881909ad2aedd1e8a78da |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:28 p.m.