Triple
T22112764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonah Mountain |
E546457
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Helen, 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: Helen, Georgia | Statement: [Yonah Mountain, near, Helen, Georgia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen, Georgia Context triple: [Yonah Mountain, near, Helen, Georgia]
-
A.
Helen, Georgia
chosen
Helen, Georgia is a small Bavarian-themed alpine village and popular tourist destination in the mountains of northeast Georgia.
-
B.
Philema, Georgia
Philema, Georgia is a small unincorporated community located in rural Lee County in the southwestern part of the state.
-
C.
Nahunta, Georgia
Nahunta, Georgia is a small city in southeastern Georgia that serves as the county seat of Brantley County.
-
D.
McRae-Helena, Georgia
McRae-Helena, Georgia is a small city in south-central Georgia that serves as the administrative and commercial hub of Telfair County.
-
E.
Homer, Georgia
Homer, Georgia is a small historic town in northeastern Georgia that serves as the administrative and cultural center of Banks County.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1294ae7608190901745384a023bab |
completed | April 28, 2026, 9:40 p.m. |
Created at: April 16, 2026, 8:31 p.m.