Triple
T15483294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Georgia |
E376975
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Jesup, Georgia |
E375203
|
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: Jesup, Georgia | Statement: [South Georgia, hasCity, Jesup, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jesup, Georgia Context triple: [South Georgia, hasCity, Jesup, Georgia]
-
A.
Jesup, Georgia
chosen
Jesup, Georgia is a small city in southeastern Georgia that serves as the county seat of Wayne County and a regional hub for rail and outdoor recreation.
-
B.
Statesboro, Georgia
Statesboro, Georgia is a small city in southeastern Georgia known as a regional hub for education, commerce, and as the home of Georgia Southern University.
-
C.
De Soto, Georgia
De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
-
D.
Cusseta, Georgia
Cusseta, Georgia is a small city in west-central Georgia that serves as the county seat of Chattahoochee County and forms a unified city-county government with it.
-
E.
St. Marys, Georgia
St. Marys, Georgia is a historic coastal town in southeastern Georgia known as a gateway to Cumberland Island and the surrounding marshes and waterways.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8e6ff08190b130b3a38f4190e7 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa9300c5481909b719b65dcf548bf |
completed | May 9, 2026, 9:37 p.m. |
Created at: April 10, 2026, 3:42 a.m.