Triple
T11311451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vidalia, Georgia |
E267844
|
entity |
| Predicate | hasOfficialName |
P66
|
FINISHED |
| Object | Vidalia |
E267844
|
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: Vidalia | Statement: [Vidalia, Georgia, hasOfficialName, Vidalia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vidalia Context triple: [Vidalia, Georgia, hasOfficialName, Vidalia]
-
A.
Vidalia, Georgia
chosen
Vidalia, Georgia is a small city in southeastern Georgia best known as the namesake and primary production area of the famous sweet Vidalia onions.
-
B.
Tift
Tift is a surname most notably associated with American politician and Confederate officer Nelson Tift, for whom Tift County, Georgia, is named.
-
C.
Mauldin
Mauldin is a city in South Carolina, United States, known as a suburban community within the Greenville metropolitan area.
-
D.
Mauldin
Mauldin is the surname of American music producer, songwriter, and record executive Jermaine Dupri.
-
E.
Toano
Toano is a small unincorporated community in eastern Virginia known for its rural character and proximity to the historic Williamsburg 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c1b7dc81908d8cc768c47390d3 |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a7fc06881909afe85a600d25ff2 |
completed | April 19, 2026, 5:01 p.m. |
Created at: April 8, 2026, 9:32 p.m.