Triple
T22192721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisconsin Rapids |
E548469
|
entity |
| Predicate | countySeatOf |
P383
|
FINISHED |
| Object | Wood 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: Wood County | Statement: [Wisconsin Rapids, countySeatOf, Wood County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wood County Context triple: [Wisconsin Rapids, countySeatOf, Wood County]
-
A.
Wood County
chosen
Wood County is a county in central Wisconsin known for its mix of small cities, agricultural areas, and paper industry heritage.
-
B.
Wood County
Wood County is a county in western West Virginia that includes the city of Vienna and is part of the Parkersburg metropolitan area along the Ohio River.
-
C.
Smith County
Smith County is a rural county in central Mississippi known for its small communities, agriculture, and pine forests.
-
D.
Smith County
Smith County is a county in eastern Texas that includes the city of Tyler and serves as a regional hub for healthcare, education, and commerce.
-
E.
Emmet County
Emmet County is a county in the northwestern Lower Peninsula of Michigan, known for its Lake Michigan shoreline, resort communities like Petoskey and Harbor Springs, and scenic natural landscapes.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae49ec881908fa42446b19e3f2d |
completed | April 28, 2026, 9:47 p.m. |
Created at: April 16, 2026, 8:35 p.m.