Triple
T15657750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanon, Georgia |
E376487
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Lebanon, GA |
E376487
|
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: Lebanon, GA | Statement: [Lebanon, Georgia, hasAbbreviation, Lebanon, GA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lebanon, GA Context triple: [Lebanon, Georgia, hasAbbreviation, Lebanon, GA]
-
A.
Lebanon, Georgia
chosen
Lebanon, Georgia is a small unincorporated community located in Cherokee County in the U.S. state of Georgia.
-
B.
Lenox, Georgia
Lenox, Georgia is a small town in southern Georgia known for its rural character and location along Interstate 75.
-
C.
Lovett, Georgia
Lovett, Georgia is a small unincorporated rural community located in Laurens County in the central part of the state.
-
D.
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.
-
E.
Sylvania, Georgia
Sylvania, Georgia is a small city in Screven County known as the county seat and a historic community in eastern Georgia.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef3cb8c8190a10815b675b341c1 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff679bb7f0819092a98c2981bc9267 |
completed | May 9, 2026, 4:58 p.m. |
Created at: April 10, 2026, 4:15 a.m.