Triple
T1534377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto streetcar system |
E32517
|
entity |
| Predicate | numberOfRoutes |
P29564
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Toronto streetcar system, numberOfRoutes, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRoutes Context triple: [Toronto streetcar system, numberOfRoutes, 10]
-
A.
numberOfRoadways
Indicates the count of distinct roadways associated with or present at a given entity or location.
-
B.
numberOfRailLines
Indicates the total count of rail lines associated with or serving a given entity.
-
C.
laneCount
Indicates the number of parallel lanes associated with a given road or roadway segment.
-
D.
northSouthRoutes
Indicates that there are routes or connections running in a generally north–south direction between the related entities.
-
E.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
- F. None of above. chosen
Provenance (4 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a915f1694081908f87b509eda1309f |
completed | March 5, 2026, 5:34 a.m. |
Created at: March 4, 2026, 7:26 p.m.