Triple
T16042634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Louise |
E389134
|
entity |
| Predicate | distanceToCalgary |
P58471
|
FINISHED |
| Object | approximately 180 kilometres west of Calgary |
—
|
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: approximately 180 kilometres west of Calgary | Statement: [Lake Louise, distanceToCalgary, approximately 180 kilometres west of Calgary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCalgary Context triple: [Lake Louise, distanceToCalgary, approximately 180 kilometres west of Calgary]
-
A.
distanceFromCalgary
chosen
Indicates the spatial distance between a given location and the city of Calgary.
-
B.
distanceToEdmonton
Indicates the spatial distance between a given entity’s location and the city of Edmonton.
-
C.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
D.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
-
E.
distanceToWinnipeg
Indicates the spatial distance between a given entity’s location and the city of Winnipeg.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.