Triple
T14209243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keysville, Georgia |
E352181
|
entity |
| Predicate | isInRuralCounty |
P45725
|
FINISHED |
| Object | Burke County, Georgia |
—
|
NE NERFINISHED |
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: Burke County, Georgia | Statement: [Keysville, Georgia, isInRuralCounty, Burke County, Georgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInRuralCounty Context triple: [Keysville, Georgia, isInRuralCounty, Burke County, Georgia]
-
A.
isRuralCounty
Indicates that a given county is classified as rural rather than urban based on demographic, geographic, or administrative criteria.
-
B.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
C.
isInRuralAreaOf
chosen
Indicates that one entity is located within the rural area or countryside region associated with another entity.
-
D.
isRuralRegion
Indicates that a region is classified as rural, typically characterized by low population density and limited urban development.
-
E.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61fa8d24819092a8ec5d34c1c799 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:05 a.m.