Triple
T34808403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coloma Charter Township, Michigan |
E1003429
|
entity |
| Predicate | isLandUse |
P38195
|
FINISHED |
| Object | primarily residential and rural |
—
|
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: primarily residential and rural | Statement: [Coloma Charter Township, Michigan, isLandUse, primarily residential and rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLandUse Context triple: [Coloma Charter Township, Michigan, isLandUse, primarily residential and rural]
-
A.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
B.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
-
C.
majorLandUse
chosen
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
D.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
E.
servesLandUseType
Indicates that one entity functions to support, accommodate, or provide services for a specified land use type.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 3:59 p.m.