Triple
T9164535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dawsonville |
E219916
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | Dawsonville, USA |
E219916
|
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: Dawsonville, USA | Statement: [Dawsonville, hasNickname, Dawsonville, USA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dawsonville, USA Context triple: [Dawsonville, hasNickname, Dawsonville, USA]
-
A.
Dawsonville
chosen
Dawsonville is a small city in north Georgia known for its gold rush history and strong ties to stock car racing and NASCAR culture.
-
B.
Dawson, Georgia
Dawson, Georgia is a small city in Terrell County known as an agricultural and regional trade center in southwest Georgia.
-
C.
Darien, Georgia
Darien, Georgia is a historic coastal city in McIntosh County known for its shrimping industry and scenic marshlands along the Atlantic coast.
-
D.
Valdosta, Georgia
Valdosta, Georgia is a small city in southern Georgia known as a regional hub for education, retail, and sports, particularly high school football.
-
E.
Montezuma, Georgia
Montezuma, Georgia is a small city in central Georgia known as the largest municipality in Macon County and part of the broader Americus–Cordele–Vienna combined statistical area.
- 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2ee64c8190a9a5abafe5d0b086 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05484c2688190a5c64b5b54bedbb5 |
completed | April 4, 2026, midnight |
Created at: March 30, 2026, 7:21 p.m.