Triple
T20089199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayland Township, Allegan County, Michigan |
E496220
|
entity |
| Predicate | borderTypeWithWayland |
P138676
|
FINISHED |
| Object | township–city boundary |
—
|
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: township–city boundary | Statement: [Wayland Township, Allegan County, Michigan, borderTypeWithWayland, township–city boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTypeWithWayland Context triple: [Wayland Township, Allegan County, Michigan, borderTypeWithWayland, township–city boundary]
-
A.
borderArea
Indicates that an area lies along or near the boundary between two regions, countries, or territories.
-
B.
borderWithin
Indicates that one region’s border lies entirely inside the boundary of another region.
-
C.
sharesBorderType
Indicates that two entities are connected by a common boundary characterized by the same specified type of border (e.g., land, river, maritime).
-
D.
borderColor
Indicates the color that forms the boundary or outline of an entity.
-
E.
hadBorderType
Indicates that a boundary between two entities existed and specifies the nature or classification of that border (e.g., land, maritime, disputed).
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655d65a88190a510132f36341b6c |
completed | April 20, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 11:18 p.m.