Triple
T905388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talbot County, Georgia |
E19535
|
entity |
| Predicate | isRuralCounty |
P22546
|
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: [Talbot County, Georgia, isRuralCounty, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRuralCounty Context triple: [Talbot County, Georgia, isRuralCounty, true]
-
A.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
B.
isSuburbanCounty
Indicates that a county is classified as suburban, typically lying outside a central city and characterized by intermediate population density and development.
-
C.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
D.
isUrbanCounty
Indicates that a county is classified as urban, typically based on population density, development level, or similar urbanization criteria.
-
E.
isRuralServiceTown
Indicates that a town functions primarily as a service and support center for surrounding rural or agricultural areas.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b28ff5948190982c4439eadf9d87 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b3bab5788190a62a0e23a698f7c7 |
completed | March 1, 2026, 9:46 p.m. |
Created at: March 1, 2026, 7:39 p.m.