Triple
T11370135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roseau County |
E269318
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Beltrami County |
E866736
|
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: Beltrami County | Statement: [Roseau County, borders, Beltrami County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beltrami County Context triple: [Roseau County, borders, Beltrami County]
-
A.
Beltrami County
chosen
Beltrami County is a county in northern Minnesota known for its extensive forests, lakes, and outdoor recreation areas.
-
B.
Roseau County
Roseau County is a rural county in northwestern Minnesota known for its agriculture, forests, and proximity to the Canadian border.
-
C.
Winnebago County
Winnebago County is a county in northern Illinois whose largest city and county seat is Rockford.
-
D.
Winnebago County
Winnebago County is a county in east-central Wisconsin that includes cities such as Oshkosh and Neenah along the western shore of Lake Winnebago.
-
E.
Steele County
Steele County is a rural county in eastern North Dakota known for its agricultural landscape and small, close-knit communities.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea89e1148190b0ca29db9d7e2cbd |
completed | April 9, 2026, 6:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e603bbb84c81908a29fcef32d3cf31 |
completed | April 20, 2026, 10:45 a.m. |
Created at: April 8, 2026, 9:33 p.m.