Triple
T1326079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idaho |
E28328
|
entity |
| Predicate | hasBorderLengthWithCanada_km |
P26571
|
FINISHED |
| Object | 72 |
—
|
LITERAL 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: 72 | Statement: [Idaho, hasBorderLengthWithCanada_km, 72]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderLengthWithCanada_km Context triple: [Idaho, hasBorderLengthWithCanada_km, 72]
-
A.
hasBorderLengthWithUSA
Indicates that the length of the land or maritime border shared between a given country or region and the USA has a specified measurement.
-
B.
longestLandBorderWith
Indicates that two entities share a land border and that this border is the longest land border for at least one of the entities.
-
C.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
D.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
-
E.
borderedBy
Indicates that one entity shares a common boundary or edge with another entity.
- F. None of above. chosen
Provenance (4 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19fd2648190932a85eacb3e7ec4 |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:55 p.m.