Triple
T23663809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calhoun County, Georgia |
E584521
|
entity |
| Predicate | hasISOSubdivisionCode |
P189
|
FINISHED |
| Object | US-GA |
—
|
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: US-GA | Statement: [Calhoun County, Georgia, hasISOSubdivisionCode, US-GA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISOSubdivisionCode Context triple: [Calhoun County, Georgia, hasISOSubdivisionCode, US-GA]
-
A.
hasSubdivisionCode
Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
-
B.
hasSubdivisionCodePart
Indicates that an entity’s subdivision code includes or is composed of the referenced code segment or component.
-
C.
hasSubdivisionStandard
Indicates that a governing standard or specification defines how an entity is to be subdivided into smaller parts or units.
-
D.
hasISOCode
chosen
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
-
E.
hasISOCodeLevel
Indicates that an entity is associated with a specific level or tier within an ISO (International Organization for Standardization) coding system.
- 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_69e24901421881908c17a5293bdd4a8e |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b40a1284819087cd29c9c390549d |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.