Triple
T19443726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Odum, Georgia |
E486417
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Odum, Georgia |
—
|
NE NERFINISHED |
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: Odum, Georgia | Statement: [Odum, Georgia, hasName, Odum, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Odum, Georgia Context triple: [Odum, Georgia, hasName, Odum, Georgia]
-
A.
Odum, Georgia
chosen
Odum, Georgia is a small town in southeastern Georgia, United States, located in Wayne County.
-
B.
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.
-
C.
Guyton, Georgia
Guyton, Georgia is a small city in southeastern Georgia known for its historic charm and role as a residential community within the Savannah metropolitan area.
-
D.
Tallapoosa, Georgia
Tallapoosa, Georgia is a small city in Haralson County in western Georgia, known for its historic downtown and location near the Alabama state line.
-
E.
De Soto, Georgia
De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63387e2048190bfb13fea434ddb46 |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.