Triple
T6035839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baker County, Georgia |
E134417
|
entity |
| Predicate | USStateCountyCode |
P10086
|
FINISHED |
| Object | GA-07 |
—
|
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: GA-07 | Statement: [Baker County, Georgia, USStateCountyCode, GA-07]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: USStateCountyCode Context triple: [Baker County, Georgia, USStateCountyCode, GA-07]
-
A.
hasCountyCode
chosen
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
B.
USStateSubdivision
Indicates that one entity is an administrative subdivision (such as a county, parish, or borough) within a U.S. state represented by the other entity.
-
C.
stateSubdivisionCode
Indicates the standardized code that identifies a specific subdivision (such as a state, province, or region) within a larger country or territory.
-
D.
hasNumberOfCounties
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
E.
keyUSState
Indicates that a U.S. state plays a primary or strategically important role in a given context (such as politics, economy, or policy).
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b4e3ec819089b2d119ea2953fe |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:08 p.m.