Triple
T25418093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal York Road |
E636900
|
entity |
| Predicate | runsThroughNeighbourhood |
P27125
|
FINISHED |
| Object | The Queensway |
—
|
NE NERFINISHED |
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: The Queensway | Statement: [Royal York Road, runsThroughNeighbourhood, The Queensway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runsThroughNeighbourhood Context triple: [Royal York Road, runsThroughNeighbourhood, The Queensway]
-
A.
runsThroughNeighborhood
chosen
Indicates that something (such as a route, path, or service) passes through or traverses a particular neighborhood.
-
B.
routeStartNeighborhood
Indicates that a route begins within a particular neighborhood.
-
C.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
D.
operatedInNeighborhood
Indicates that an entity conducted its activities or operations within a specific neighborhood.
-
E.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area 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_69e75db4135881909acc287ebcb7a505 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5b013596c81909af7acebfc72bfc6 |
completed | May 2, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 1:55 p.m.