Triple
T11320550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brownsville Township, Minnesota |
E268081
|
entity |
| Predicate | hasCounty |
P285
|
FINISHED |
| Object | Fillmore County |
E921189
|
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: Fillmore County | Statement: [Brownsville Township, Minnesota, hasCounty, Fillmore County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fillmore County Context triple: [Brownsville Township, Minnesota, hasCounty, Fillmore County]
-
A.
Fillmore County
chosen
Fillmore County is a rural county in southeastern Minnesota known for its rolling farmland, small towns, and karst landscapes with caves and sinkholes.
-
B.
Valley County
Valley County is a mountainous county in central Idaho known for its extensive forests, outdoor recreation, and inclusion of large portions of Boise National Forest.
-
C.
Steele County
Steele County is a rural county in eastern North Dakota known for its agricultural landscape and small, close-knit communities.
-
D.
Taney County
Taney County is a county in southwestern Missouri known for encompassing the popular tourist destination city of Branson.
-
E.
Utena County
Utena County is an administrative region in northeastern Lithuania known for its lakes, forests, and river landscapes.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9de875481908acfa56015d4b46f |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58b4ec4ac81908d51e3815a054704 |
completed | April 20, 2026, 2:11 a.m. |
Created at: April 8, 2026, 9:32 p.m.