Triple
T12519670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaletown–Roundhouse station |
E299281
|
entity |
| Predicate | servesTransitMode |
P28705
|
FINISHED |
| Object | metro |
—
|
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: metro | Statement: [Yaletown–Roundhouse station, servesTransitMode, metro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesTransitMode Context triple: [Yaletown–Roundhouse station, servesTransitMode, metro]
-
A.
servesTransitFacility
Indicates that one entity provides service or operational support to a transit facility, such as a station, stop, or terminal.
-
B.
transportationServedBy
Indicates that a transportation facility, route, or area is provided service or coverage by a specific transportation provider or mode.
-
C.
publicTransitMode
chosen
Indicates the type of public transportation (e.g., bus, train, subway) used or associated with a given trip or segment.
-
D.
appliesToTransportMode
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
-
E.
hasPublicTransitServiceLevel
Indicates the level or quality of public transit service provided to or available at a given location or entity.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.