Triple
T22192787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wood County, Wisconsin |
E548470
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Hiles, Wisconsin |
—
|
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: Hiles, Wisconsin | Statement: [Wood County, Wisconsin, hasTown, Hiles, Wisconsin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hiles, Wisconsin Context triple: [Wood County, Wisconsin, hasTown, Hiles, Wisconsin]
-
A.
Hillsboro, Wisconsin
Hillsboro, Wisconsin is a small rural city in southwestern Wisconsin known for its agricultural community and local festivals.
-
B.
Hilbert, Wisconsin
Hilbert, Wisconsin is a small village in Calumet County known for its rural character and tight-knit community in east-central Wisconsin.
-
C.
Hewitt, Wisconsin
Hewitt, Wisconsin is a small rural village located in Wood County in the central part of the state.
-
D.
Hansen, Wisconsin
chosen
Hansen, Wisconsin is a small rural town located in Wood County in the central part of the state.
-
E.
Elkhorn, Wisconsin
Elkhorn, Wisconsin is a small city in southeastern Wisconsin known as the administrative and commercial hub of Walworth County.
- 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.