Triple
T485842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fayette County, Georgia |
E9874
|
entity |
| Predicate | areaWaterPercent |
P475
|
FINISHED |
| Object | small percentage of total area |
—
|
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: small percentage of total area | Statement: [Fayette County, Georgia, areaWaterPercent, small percentage of total area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaWaterPercent Context triple: [Fayette County, Georgia, areaWaterPercent, small percentage of total area]
-
A.
areaWater
chosen
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
B.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
C.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
D.
bodyOfWater
Indicates that one entity is a body of water that is geographically or physically associated with another entity.
-
E.
locatedInBodyOfWater
Indicates that an entity is situated within or on the surface of a specific body of water.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0bb46788190b40182bf2a54f98f |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf48ec08190b85d07e194f99c49 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.