Triple
T15825126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kewaunee County, Wisconsin |
E383718
|
entity |
| Predicate | hasLakesideCommunities |
P33430
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Kewaunee County, Wisconsin, hasLakesideCommunities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakesideCommunities Context triple: [Kewaunee County, Wisconsin, hasLakesideCommunities, true]
-
A.
hasShorelineCommunity
chosen
Indicates that a place or region includes or is associated with a community located along its shoreline.
-
B.
hasWaterfrontHomes
Indicates that a place or area includes residential properties located directly along a body of water.
-
C.
hasLakeshore
Indicates that one entity is located along or directly borders the shore of a lake associated with another entity.
-
D.
hasLocalCommunities
Indicates that an entity is associated with or contains smaller, localized community groups within a specific area or region.
-
E.
hasWaterfrontPark
Indicates that a place or area includes or is associated with a park located directly along a body of water.
- F. None of above.
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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e602e5481908baa71c3d9b2008f |
completed | April 16, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.