Triple
T23565181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian border near Fortuna, North Dakota |
E579350
|
entity |
| Predicate | adjacentUSCounty |
P6346
|
FINISHED |
| Object | Divide 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: Divide County | Statement: [Canadian border near Fortuna, North Dakota, adjacentUSCounty, Divide County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentUSCounty Context triple: [Canadian border near Fortuna, North Dakota, adjacentUSCounty, Divide County]
-
A.
adjacentToCounty
chosen
Indicates that one county directly borders or touches another county geographically.
-
B.
hasNearbyCounty
Indicates that one county is geographically close to or directly adjacent to another county.
-
C.
adjacentCountySeat
Indicates that the county seat of one county is directly next to or bordering the county seat of another county.
-
D.
hasNearbyCountyBorder
Indicates that the borders of two counties are geographically close to each other, though not necessarily directly adjacent.
-
E.
isCornerCountyOf
Indicates that a county lies at or near the corner where two or more larger administrative regions (such as states or districts) meet.
- F. None of above.
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_69e245fe24588190888f3aec8407d8e3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af6c2930819090bc2b95725fbf18 |
completed | April 29, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69f118bcc0b08190b25a8dddfd461a0e |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:34 p.m.