Triple
T601006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester, Georgia |
E11492
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Talbot County |
E18175
|
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: Talbot County | Statement: [Manchester, Georgia, county, Talbot County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talbot County Context triple: [Manchester, Georgia, county, Talbot County]
-
A.
Talbot County
chosen
Talbot County is a county in west-central Georgia, United States, known for its rural character and historic small towns such as Talbotton.
-
B.
Mason County
Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
-
C.
Madison County
Madison County is a county in central Mississippi, located in the Jackson metropolitan area and known for its rapidly growing suburban communities.
-
D.
Dorchester County
Dorchester County is a county in South Carolina known for its proximity to Charleston and its mix of historic communities and rapidly growing suburban areas.
-
E.
Putnam County
Putnam County is a suburban county in southeastern New York State known for its lakes, forests, and commuter communities north of New York City.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d7a2180819086c7e9465a2d7432 |
completed | March 1, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a55a734f6c8190a141dafc03dd2e77 |
completed | March 2, 2026, 9:37 a.m. |
Created at: March 1, 2026, 7:35 p.m.