Triple
T28598250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burnaby Mountain |
E723833
|
entity |
| Predicate | hasCityViewpointFunction |
P100951
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Burnaby Mountain, hasCityViewpointFunction, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityViewpointFunction Context triple: [Burnaby Mountain, hasCityViewpointFunction, yes]
-
A.
hasViewingPointFor
Indicates that one entity serves as a vantage point or location from which another entity can be viewed or observed.
-
B.
hasViewpointType
Indicates that something is associated with or characterized by a particular type or category of viewpoint or perspective.
-
C.
hasViewpointConcept
Indicates that something is associated with, characterized by, or defined through a particular viewpoint, perspective, or conceptual stance.
-
D.
cityView
chosen
Indicates that one entity offers a view of, or overlooks, a city.
-
E.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
- 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_69f01d80b1908190980594837604b8c7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 28, 2026, 4:22 a.m.