Triple
T20601277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Field, British Columbia |
E506185
|
entity |
| Predicate | distanceToLakeLouise_km |
P121660
|
FINISHED |
| Object | approximately 27 |
—
|
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 27 | Statement: [Field, British Columbia, distanceToLakeLouise_km, approximately 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLakeLouise_km Context triple: [Field, British Columbia, distanceToLakeLouise_km, approximately 27]
-
A.
distanceFromLakeLouiseVillage
chosen
Indicates the spatial distance separating an entity from Lake Louise Village.
-
B.
distanceToBanff
Indicates the measured or estimated distance between a given location or entity and Banff.
-
C.
distanceFromCalgary
Indicates the spatial distance between a given location and the city of Calgary.
-
D.
distanceFromFortWilliam
Indicates the measured distance between an entity and Fort William.
-
E.
distanceFromSquamish
Indicates the measured spatial distance between a given entity and the location of Squamish.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1ffd088190adeacb9fe4907530 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.