Triple
T13284221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Fulton County |
E316396
|
entity |
| Predicate | hasTypeOfGovernmentUnits |
P32279
|
FINISHED |
| Object | incorporated cities |
—
|
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: incorporated cities | Statement: [North Fulton County, hasTypeOfGovernmentUnits, incorporated cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGovernmentUnits Context triple: [North Fulton County, hasTypeOfGovernmentUnits, incorporated cities]
-
A.
governmentalUnitType
chosen
Indicates the specific category or classification of a governmental unit (such as federal, state, municipal, or other administrative level) that an entity belongs to.
-
B.
typeOfGovernmentInstitution
Indicates that one entity is a government institution of the type or category specified by the other entity.
-
C.
governmentalUnit
Indicates that one entity functions as a governmental or administrative unit in relation to another entity.
-
D.
hasGovernmentTypeCountry
Indicates that a country possesses or is characterized by a particular form or type of government.
-
E.
targetGovernmentType
Indicates the form or system of governance that an entity is directed toward, associated with, or intended to influence.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:27 p.m.