Triple
T30234227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Ness Avenue, San Francisco |
E768713
|
entity |
| Predicate | hasBRTInfrastructure |
P157378
|
FINISHED |
| Object | center-running bus lanes |
—
|
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: center-running bus lanes | Statement: [Van Ness Avenue, San Francisco, hasBRTInfrastructure, center-running bus lanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBRTInfrastructure Context triple: [Van Ness Avenue, San Francisco, hasBRTInfrastructure, center-running bus lanes]
-
A.
hasBRTLine
Indicates that a bus rapid transit (BRT) line is present, operates on, or serves the referenced entity.
-
B.
hasBusRapidTransitFeatures
chosen
Indicates that a transportation route or corridor includes design or operational elements characteristic of bus rapid transit systems.
-
C.
hasPublicTransitInfrastructure
Indicates that a location or area is equipped with facilities and systems that support public transportation services (e.g., buses, trains, trams).
-
D.
hasTramway
Indicates that a location or area is served by, contains, or is connected to a tramway system.
-
E.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 29, 2026, 7:37 p.m.