Triple
T34720708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Superior iron ranges |
E1000903
|
entity |
| Predicate | adjacentStateOrProvince |
P88549
|
FINISHED |
| Object | Minnesota |
—
|
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: Minnesota | Statement: [Lake Superior iron ranges, adjacentStateOrProvince, Minnesota]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStateOrProvince Context triple: [Lake Superior iron ranges, adjacentStateOrProvince, Minnesota]
-
A.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
-
B.
adjacentCanadianProvince
Indicates that two entities are Canadian provinces that share a common land or maritime border.
-
C.
adjacentToCanadianProvince
Indicates that one entity is directly next to or shares a border with a Canadian province.
-
D.
nearbyStateOrProvince
Indicates that one state or province is geographically close to, but not necessarily directly bordering, another state or province.
-
E.
borderingStateOrProvince
chosen
Indicates that one state or province shares a common boundary with another state or province.
- 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_69f76daeb6e48190a4c9a6b0edc80f72 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 3:59 p.m.