Triple
T6484912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bullock County |
E146483
|
entity |
| Predicate | formedFrom |
P402
|
FINISHED |
| Object | Macon County |
E191331
|
NE 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: Macon County | Statement: [Bullock County, formedFrom, Macon County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macon County Context triple: [Bullock County, formedFrom, Macon County]
-
A.
Macon County
Macon County is a rural county in central Georgia known for its agricultural landscape and small-town communities.
-
B.
Macon County
chosen
Macon County is a county in eastern Alabama known for its historical significance in the civil rights movement and as the home of Tuskegee University.
-
C.
Marshall County
Marshall County is a county in northern Alabama known for its scenic location around Lake Guntersville and its mix of small towns and rural communities.
-
D.
Fayette County
Fayette County is a largely rural county in southwestern Pennsylvania known for its Appalachian landscape, historic industrial and coal-mining heritage, and proximity to the Pittsburgh metropolitan area.
-
E.
Fayette County
Fayette County is a rural county in western Alabama known for its small-town communities and agricultural and forestry-based economy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a6efe1881909a044b1cdaa511af |
completed | March 22, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e40c193c8190b4d7acd4530121f0 |
completed | March 27, 2026, 8:09 p.m. |
Created at: March 22, 2026, 4:52 p.m.