Triple
T417013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton Township, DuPage County, Illinois |
E8014
|
entity |
| Predicate | suburban |
P9847
|
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: [Milton Township, DuPage County, Illinois, suburban, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburban Context triple: [Milton Township, DuPage County, Illinois, suburban, true]
-
A.
hasSuburbanCharacter
chosen
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
B.
isResidentialSuburbOf
Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
-
C.
town
Indicates that a location is classified or functions as a town within a given geographic or administrative context.
-
D.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
E.
withinUrbanArea
Indicates that one entity is located inside the spatial boundaries of an urban area associated with another entity.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd1ca148190a66bd8c5aad867d5 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.