Triple
T10630000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warren Township |
E250426
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Poweshiek County |
E851250
|
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: Poweshiek County | Statement: [Warren Township, county, Poweshiek County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Poweshiek County Context triple: [Warren Township, county, Poweshiek County]
-
A.
Poweshiek County
chosen
Poweshiek County is a rural county in central Iowa known for its agricultural landscape and small communities, including the town of Deep River.
-
B.
Waushara County
Waushara County is a rural county in central Wisconsin known for its lakes, forests, and outdoor recreation.
-
C.
Winneshiek County
Winneshiek County is a county in northeastern Iowa known for its scenic Driftless Area landscape, Norwegian-American heritage, and county seat of Decorah.
-
D.
Ogemaw County
Ogemaw County is a rural county in the northeastern Lower Peninsula of Michigan, known for its forests, lakes, and outdoor recreation opportunities.
-
E.
Bayfield County
Bayfield County is a county in northern Wisconsin known for its Lake Superior shoreline, Apostle Islands, and extensive outdoor recreation opportunities.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df93a2b88190a0f3a52b8e88f54f |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e343cd76448190b0583cc15005ac9d |
completed | April 18, 2026, 8:41 a.m. |
Created at: April 8, 2026, 9 p.m.