Triple
T8402299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dacula, Georgia |
E198402
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Auburn, Georgia |
E170316
|
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: Auburn, Georgia | Statement: [Dacula, Georgia, near, Auburn, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Auburn, Georgia Context triple: [Dacula, Georgia, near, Auburn, Georgia]
-
A.
Auburn, Georgia
chosen
Auburn, Georgia is a small city in Barrow and Gwinnett counties within the Atlanta metropolitan area.
-
B.
Auburn
Auburn is a small city in northeastern Indiana known for its automotive heritage and classic car museums.
-
C.
Auburn
Auburn is a city in eastern Alabama known for being home to Auburn University and its strong college-town atmosphere.
-
D.
Auburn
Auburn is a small city in southeastern Nebraska that serves as the county seat of Nemaha County and a local hub for the surrounding rural region.
-
E.
Auburn
Auburn is a small historic town in South Australia's Clare Valley, known as a gateway to the wine region and a base for visitors exploring local vineyards and heritage sites.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb824efa5c81908ce816cdb8e1fcfb |
completed | March 31, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce02e129bc819081e6ea2dd43becba |
completed | April 2, 2026, 5:47 a.m. |
Created at: March 30, 2026, 6:04 p.m.