Triple
T20155992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candler County |
E491566
|
entity |
| Predicate | bordersOn |
P224
|
FINISHED |
| Object | Evans County |
—
|
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: Evans County | Statement: [Candler County, bordersOn, Evans County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evans County Context triple: [Candler County, bordersOn, Evans County]
-
A.
Evans County
chosen
Evans County is a rural county in southeastern Georgia known for its agricultural landscape and small-town communities.
-
B.
Kelan County
Kelan County is a county in Xinzhou, Shanxi Province, China, known for its proximity to the Taiyuan Satellite Launch Center, one of the country’s major space launch facilities.
-
C.
Taylor County
Taylor County is a rural county in southwestern Iowa known for its agricultural landscape and small communities.
-
D.
Taylor County
Taylor County is a rural county in west-central Georgia known for its small communities, agricultural landscape, and location along key state highways.
-
E.
Taylor County
Taylor County is a rural county in Florida known for its Gulf Coast shoreline, forests, and small-town communities centered around the city of Perry.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e0a0488190a25d92aaf300be4a |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.