Triple
T12089146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Washington, Kentucky |
E287891
|
entity |
| Predicate | isGrowingSuburb |
P22501
|
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: [Mount Washington, Kentucky, isGrowingSuburb, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isGrowingSuburb Context triple: [Mount Washington, Kentucky, isGrowingSuburb, true]
-
A.
hasSuburbanGrowth
chosen
Indicates that an area or entity is experiencing or characterized by expansion or development typical of suburban environments.
-
B.
isIndustrialSuburbOf
Indicates that one place is a suburb characterized by industrial land use and functions that is located within or adjacent to another, typically larger, urban area.
-
C.
isResidentialSuburbOf
Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
-
D.
suburb
Indicates that one place is a residential district or outlying area that is part of or adjacent to a larger city or town.
-
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.
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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.