Triple
T5825319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaston College |
E129207
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Gaston County |
E172603
|
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: Gaston County | Statement: [Gaston College, serves, Gaston County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaston County Context triple: [Gaston College, serves, Gaston County]
-
A.
Gaston County
chosen
Gaston County is a county in North Carolina that forms part of the greater Charlotte metropolitan region, combining suburban communities with industrial and natural areas.
-
B.
Cabarrus County
Cabarrus County is a North Carolina county in the Charlotte metropolitan area known for its rapidly growing suburbs and the Charlotte Motor Speedway.
-
C.
Catawba County
Catawba County is a county in western North Carolina known for its manufacturing base and inclusion in the greater Charlotte metropolitan region.
-
D.
Nash County
Nash County is a county in eastern North Carolina known for its mix of rural communities, small towns like Rocky Mount, and agricultural and manufacturing-based economy.
-
E.
Iredell County
Iredell County is a county in North Carolina known for its mix of suburban communities, transportation corridors, and proximity to the city of Charlotte.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0341a85988190be988f1c0722da66 |
completed | March 22, 2026, 6:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9c89d62c08190b575d7e1058afbeb |
completed | March 30, 2026, 12:49 a.m. |
Created at: March 22, 2026, 3:53 p.m.