Triple
T458407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 Yonge–University |
E7281
|
entity |
| Predicate | isBusiestLineInSystem |
P5905
|
FINISHED |
| Object | Toronto subway |
—
|
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: Toronto subway | Statement: [Line 1 Yonge–University, isBusiestLineInSystem, Toronto subway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBusiestLineInSystem Context triple: [Line 1 Yonge–University, isBusiestLineInSystem, Toronto subway]
-
A.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
B.
lineServed
Indicates that a particular transportation line (such as a bus, train, or metro line) provides service to or is operated at a given stop, station, or route segment.
-
C.
isBusiestPassengerRailLineIn
chosen
Indicates that a passenger rail line is the one with the highest level of use or traffic within a specified geographic area or system.
-
D.
servedByLine
Indicates that a transportation stop, station, or location is provided service by a specific transit line.
-
E.
line8Status
Indicates the status or condition associated with the eighth line in a sequence, record, or structured data set.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa3163081909acff040a22bd559 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede75b6c81908350103d21f22a03 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.