Triple
T2602907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pine Valley Drive |
E58385
|
entity |
| Predicate | hasIntersectionsWith |
P13379
|
FINISHED |
| Object | other local and arterial roads in Vaughan |
—
|
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: other local and arterial roads in Vaughan | Statement: [Pine Valley Drive, hasIntersectionsWith, other local and arterial roads in Vaughan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntersectionsWith Context triple: [Pine Valley Drive, hasIntersectionsWith, other local and arterial roads in Vaughan]
-
A.
hasNotableIntersection
chosen
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
B.
overlapsWith
Indicates that two entities share a common part or region in space, time, or extent, but neither is completely contained within the other.
-
C.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
D.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
-
E.
collidesWith
Indicates that two entities come into contact with each other in space, typically implying an impact or physical intersection of their paths or volumes.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd48241c48190bc80418212e33bc8 |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0d4e8648190b612eb09aa085451 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.