Triple
T19806218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Douglas |
E475817
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Allegan County |
—
|
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: Allegan County | Statement: [City of Douglas, county, Allegan County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allegan County Context triple: [City of Douglas, county, Allegan County]
-
A.
Allegan County
chosen
Allegan County is a county in southwestern Michigan known for its mix of Lake Michigan shoreline, agricultural land, and small towns.
-
B.
Huron County
Huron County is a predominantly rural county in southwestern Ontario, Canada, known for its agriculture, small towns, and Lake Huron shoreline.
-
C.
Huron County
Huron County is a county in northern Ohio known for its mix of small cities, rural communities, and agricultural land.
-
D.
Barry County
Barry County is a rural county in southwestern Michigan known for its lakes, forests, and small communities between the Grand Rapids and Kalamazoo metropolitan areas.
-
E.
Waushara County
Waushara County is a rural county in central Wisconsin known for its lakes, forests, and outdoor recreation.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428081c8190b394c442f4c2a9a6 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.