Triple
T25787762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario Highway 401 |
E649466
|
entity |
| Predicate | busiestSection |
P66624
|
FINISHED |
| Object | through Toronto |
—
|
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: through Toronto | Statement: [Ontario Highway 401, busiestSection, through Toronto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: busiestSection Context triple: [Ontario Highway 401, busiestSection, through Toronto]
-
A.
oneOfBusiestStationsIn
Indicates that a station is among the busiest stations within a specified area or system.
-
B.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
C.
isOneOfBusiestStopsOn
Indicates that a stop ranks among the most heavily used or frequently served stops on a given route or line.
-
D.
isMostHeavilyTraveledCorridorIn
chosen
Indicates that a particular route or corridor experiences the highest volume of travel or traffic within a specified area or region.
-
E.
isBusiestTerminalOf
Indicates that one terminal is the busiest (i.e., handles the highest volume of activity) among all terminals associated with a given entity, such as an airport or transportation hub.
- 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_69e7ab33e9308190afe415dc6f9e8876 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fefc58ac8190a770987f2b7b641b |
completed | May 2, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 5:56 a.m.