Triple
T21688037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stonyford |
E535282
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Colusa 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: Colusa County | Statement: [Stonyford, locatedIn, Colusa County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colusa County Context triple: [Stonyford, locatedIn, Colusa County]
-
A.
Colusa County
chosen
Colusa County is a rural county in California’s Sacramento Valley known for its agricultural economy and small, historic communities.
-
B.
Treasure County
Treasure County is a sparsely populated rural county in south-central Montana known for its agricultural landscape along the Yellowstone River.
-
C.
Gem County
Gem County is a county in southwestern Idaho that forms part of the Boise metropolitan area.
-
D.
Lewis and Clark County
Lewis and Clark County is a county in west-central Montana, United States, known for encompassing the state capital city of Helena.
-
E.
Fillmore County
Fillmore County is a rural county in southeastern Minnesota known for its rolling farmland, small towns, and karst landscapes with caves and sinkholes.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cd51d481908df67e4f69826b06 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:44 p.m.