Triple
T21166062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaverlodge |
E521565
|
entity |
| Predicate | distanceToGrandePrairie_km |
P143134
|
FINISHED |
| Object | approximately 43 |
—
|
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 43 | Statement: [Beaverlodge, distanceToGrandePrairie_km, approximately 43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGrandePrairie_km Context triple: [Beaverlodge, distanceToGrandePrairie_km, approximately 43]
-
A.
distanceFromCalgary
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.
distanceToWinnipeg
Indicates the spatial distance between a given entity’s location and the city of Winnipeg.
-
D.
distanceToMontreal
Indicates the spatial distance between a given entity’s location and the city of Montreal.
-
E.
distanceFromQuebecCity
Indicates the measured distance between a given place or object and Quebec City.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7270efe3081908a50fc601c2f958c |
completed | April 21, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f993240c8190847c0b08e65726c8 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 2:59 p.m.