Triple
T15540653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roswell King |
E370464
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Darien, Georgia |
E377640
|
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: Darien, Georgia | Statement: [Roswell King, workLocation, Darien, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darien, Georgia Context triple: [Roswell King, workLocation, Darien, Georgia]
-
A.
Darien, Georgia
chosen
Darien, Georgia is a historic coastal city in McIntosh County known for its shrimping industry and scenic marshlands along the Atlantic coast.
-
B.
Vidette, Georgia
Vidette, Georgia is a small unincorporated rural community located in Burke County in the eastern part of the state.
-
C.
Screven, Georgia
Screven, Georgia is a small rural town in southeastern Georgia known for its quiet community and location within Wayne County.
-
D.
Folkston, Georgia
Folkston, Georgia is a small city in southeastern Georgia known as a gateway to the Okefenokee Swamp and a popular spot for train watching.
-
E.
Union Point, Georgia
Union Point, Georgia is a small historic city in Greene County known for its railroad heritage and preserved 19th-century architecture.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04430b5188190a555a3cd4fb0c61c |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe6287f48190a54d0d029dc503f8 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:07 a.m.