Triple
T410251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coweta County, Georgia |
E9472
|
entity |
| Predicate | locatedInCensusRegion |
P5151
|
FINISHED |
| Object | South |
—
|
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: South | Statement: [Coweta County, Georgia, locatedInCensusRegion, South]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCensusRegion Context triple: [Coweta County, Georgia, locatedInCensusRegion, South]
-
A.
censusRegion
chosen
Indicates the broader census-defined geographic region in which an entity (such as a place or population unit) is located or classified.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
demographicRegion
Indicates that an entity is associated with, belongs to, or is characterized by a particular geographic or administrative region for demographic purposes.
-
D.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
E.
regionName
Indicates the name assigned to a specific geographic or administrative region.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.