Triple
T946796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaver County |
E20430
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Butler County |
E20762
|
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: Butler County | Statement: [Beaver County, borderedBy, Butler County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Butler County Context triple: [Beaver County, borderedBy, Butler County]
-
A.
Butler County
chosen
Butler County is a county in western Pennsylvania, north of Pittsburgh, known for its mix of suburban communities, rural landscapes, and growing industrial and service sectors.
-
B.
Butler County
Butler County is a rural county in south-central Alabama known for its pine forests, small towns, and location along the Interstate 65 corridor.
-
C.
Marshall County
Marshall County is a county in northern Alabama known for its scenic location around Lake Guntersville and its mix of small towns and rural communities.
-
D.
Boone County
Boone County is a rural county in southern West Virginia known historically for its coal mining communities and Appalachian landscape.
-
E.
Fayette County
Fayette County is a largely rural county in southwestern Pennsylvania known for its Appalachian landscape, historic industrial and coal-mining heritage, and proximity to the Pittsburgh metropolitan area.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae3032c1588190bae02f0e2152c6f1 |
completed | March 9, 2026, 2:28 a.m. |
Created at: March 1, 2026, 7:40 p.m.