Triple
T4730044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumter County, Georgia |
E104982
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Leslie, Georgia |
E167203
|
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: Leslie, Georgia | Statement: [Sumter County, Georgia, hasTown, Leslie, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leslie, Georgia Context triple: [Sumter County, Georgia, hasTown, Leslie, Georgia]
-
A.
Leslie, Georgia
chosen
Leslie, Georgia is a small rural city in southwest Georgia known for its agricultural surroundings and tight-knit community.
-
B.
Leary, Georgia
Leary, Georgia is a small rural city located in southwestern Georgia within Calhoun County.
-
C.
De Soto, Georgia
De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
-
D.
Bogart, Georgia
Bogart, Georgia is a small town in northeastern Georgia located near the Athens metropolitan area.
-
E.
Williamson, Georgia
Williamson, Georgia is a small rural city located in Pike County in the west-central part of the U.S. state of 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd646135c881909030c21a163cc619 |
completed | March 20, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be10a4bc0481908935278afb13503d |
completed | March 21, 2026, 3:29 a.m. |
Created at: March 20, 2026, 1:19 p.m.