Triple
T18602102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crow Wing County |
E454642
|
entity |
| Predicate | countySeat |
P383
|
FINISHED |
| Object | Brainerd |
—
|
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: Brainerd | Statement: [Crow Wing County, countySeat, Brainerd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brainerd Context triple: [Crow Wing County, countySeat, Brainerd]
-
A.
Brainerd
chosen
Brainerd is a small city in central Minnesota, United States, known as a regional hub for outdoor recreation in the lakes area.
-
B.
Fridley
Fridley is a suburban city in Anoka County, Minnesota, located just north of Minneapolis along the Mississippi River.
-
C.
Hibbing
Hibbing is a city in northern Minnesota known for its rich iron mining history and as the hometown of musician Bob Dylan.
-
D.
Minnetonka
Minnetonka is a suburban city in the Minneapolis–Saint Paul metropolitan area of Minnesota, known for its residential communities and proximity to Lake Minnetonka.
-
E.
Wayzata
Wayzata is a small, affluent lakeside city in Minnesota known for its location on the shores of Lake Minnetonka and its upscale residential and recreational 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54751d7ec81909efc4867f649002e |
completed | April 19, 2026, 9:21 p.m. |
Created at: April 10, 2026, 11:45 a.m.