Triple
T28949560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Vancouver from the North Shore |
E730969
|
entity |
| Predicate | showsContrastBetween |
P76521
|
FINISHED |
| Object | urban skyline and coastal water |
—
|
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: urban skyline and coastal water | Statement: [City of Vancouver from the North Shore, showsContrastBetween, urban skyline and coastal water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showsContrastBetween Context triple: [City of Vancouver from the North Shore, showsContrastBetween, urban skyline and coastal water]
-
A.
providesContrastWith
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
B.
achievesContrast
chosen
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
C.
exploresContrastBetween
Indicates a relationship in which one entity examines, highlights, or analyzes the differences or oppositions between two or more entities, ideas, or situations.
-
D.
createsContrastIn
Indicates a relationship where one element is used to highlight or emphasize differences with another element within a given context.
-
E.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 8:42 a.m.