Triple
T14858594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Mounds (town) |
E349426
|
entity |
| Predicate | regionalFeature |
P74315
|
FINISHED |
| Object | driftless area of Wisconsin |
—
|
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: driftless area of Wisconsin | Statement: [Blue Mounds (town), regionalFeature, driftless area of Wisconsin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalFeature Context triple: [Blue Mounds (town), regionalFeature, driftless area of Wisconsin]
-
A.
politicalFeature
Indicates that an entity possesses a political characteristic, attribute, or aspect relevant to governance, power structures, or public policy.
-
B.
regionalComponent
chosen
Indicates that one entity functions as a sub-region or constituent part within the larger geographic or administrative area represented by the other entity.
-
C.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
D.
region1
Indicates that one entity is the first or primary region associated with, containing, or encompassing another entity.
-
E.
isRegional
Indicates that something pertains to, is characteristic of, or is limited to a specific geographic region or area.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44598e48190b759a05ed2d9ecaf |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.