Triple
T8557156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Ness–UDC station |
E202599
|
entity |
| Predicate | hasIslandPlatformServingBothDirections |
P18595
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Van Ness–UDC station, hasIslandPlatformServingBothDirections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIslandPlatformServingBothDirections Context triple: [Van Ness–UDC station, hasIslandPlatformServingBothDirections, yes]
-
A.
hasIslandPlatforms
chosen
Indicates that the subject has one or more island-style platforms, typically positioned between tracks and accessible from both sides.
-
B.
hasTwoOperationalDirections
Indicates that an entity supports or functions in two distinct operational directions or modes.
-
C.
hasRailPlatforms
Indicates that an entity is equipped with one or more rail platforms used for boarding or alighting from trains.
-
D.
hasSidePlatforms
Indicates that something is equipped with platforms located on its sides, typically for access, support, or operation.
-
E.
hasBayPlatforms
Indicates that a station or terminal is equipped with bay platforms, where tracks end in a dead-end configuration and trains enter and exit from the same direction.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe946d1408190adc7dfb7b2173f9d |
completed | March 31, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69cbd1160fcc8190aa380a73610af731 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.