Triple
T12929659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lansing Township, Michigan |
E309340
|
entity |
| Predicate | isPartiallyUrbanized |
P107069
|
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: [Lansing Township, Michigan, isPartiallyUrbanized, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartiallyUrbanized Context triple: [Lansing Township, Michigan, isPartiallyUrbanized, true]
-
A.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
B.
isLessUrbanizedThan
Indicates that one place has a lower degree of urban development or urban characteristics compared to another place.
-
C.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
-
D.
isUrbanizing
Indicates a process in which an area or population becomes more urban in character, typically through increased development, infrastructure, and concentration of people and activities.
-
E.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
- F. None of above. chosen
Provenance (4 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d970f6f5748190ad35aff801db53d5 |
completed | April 10, 2026, 9:51 p.m. |
Created at: April 9, 2026, 5:42 p.m.