Triple
T12519683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaletown–Roundhouse station |
E299281
|
entity |
| Predicate | hasCanopyOrCover |
P8429
|
FINISHED |
| Object | street-level entrance canopy |
—
|
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: street-level entrance canopy | Statement: [Yaletown–Roundhouse station, hasCanopyOrCover, street-level entrance canopy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanopyOrCover Context triple: [Yaletown–Roundhouse station, hasCanopyOrCover, street-level entrance canopy]
-
A.
hasCanopy
chosen
Indicates that one entity possesses or is characterized by a canopy associated with it.
-
B.
hasCanopyDensity
Indicates the degree to which a canopy (such as a tree or forest cover) occupies or obscures the area beneath it.
-
C.
hasCoverings
Indicates that one entity possesses or is equipped with protective or enclosing layers, surfaces, or coverings provided by another entity.
-
D.
hasTreeCanopyProtection
Indicates that an entity is subject to rules or measures that preserve, limit removal of, or otherwise protect the tree canopy associated with it.
-
E.
hasCoverFeature
Indicates that one entity serves as a prominent or featured element on the cover of another entity (such as a publication, product, or media item).
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.