Triple
T11518768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloor–Yonge intersection |
E273100
|
entity |
| Predicate | isOrientationPointInCity |
P82630
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bloor–Yonge intersection, isOrientationPointInCity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOrientationPointInCity Context triple: [Bloor–Yonge intersection, isOrientationPointInCity, true]
-
A.
isInCity
Indicates that one entity is located within the geographical boundaries of a specified city.
-
B.
hasCoordinateInCityCentreApprox
Indicates that an entity’s location is approximately within the central area of a city, based on its geographic coordinates.
-
C.
positionOnCityCircle
Indicates that one entity is located along the circular boundary or ring-shaped layout defined by a city.
-
D.
isConfluenceAtCity
Indicates that the confluence (meeting point) of two or more water bodies occurs at or within the specified city.
-
E.
isInUrbanContext
chosen
Indicates that something exists, occurs, or is situated within an urban or city-based environment or setting.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcf927081908ef89eff7ad833b0 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.