Triple
T7855776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Storm, West Virginia |
E182171
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Grant County |
E645284
|
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: Grant County | Statement: [Mount Storm, West Virginia, county, Grant County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant County Context triple: [Mount Storm, West Virginia, county, Grant County]
-
A.
Grant County
Grant County is a county in central Washington State known for its agricultural production, reservoirs, and outdoor recreation areas.
-
B.
Grant County
chosen
Grant County is a rural county in eastern West Virginia known for its mountainous terrain, outdoor recreation areas, and small communities.
-
C.
Mason County
Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
-
D.
Clinton County
Clinton County is the name of numerous counties in the United States, typically named after prominent American statesmen such as George Clinton or DeWitt Clinton.
-
E.
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.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a74592c8190b42f298e3e33617b |
completed | March 31, 2026, 12:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3394b5408190a3d540b5eede456e |
completed | April 1, 2026, 3:02 p.m. |
Created at: March 30, 2026, 4:52 p.m.