Triple
T17759945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Jersey Route 495 |
E443343
|
entity |
| Predicate | hasBusLanes |
P31631
|
FINISHED |
| Object | exclusive bus lane during peak hours |
—
|
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: exclusive bus lane during peak hours | Statement: [New Jersey Route 495, hasBusLanes, exclusive bus lane during peak hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusLanes Context triple: [New Jersey Route 495, hasBusLanes, exclusive bus lane during peak hours]
-
A.
hasDedicatedLanes
chosen
Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
-
B.
hasCarpoolLanes
Indicates that a road, route, or transportation facility includes designated carpool (high-occupancy vehicle) lanes available for use.
-
C.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
D.
hasWheelchairLanes
Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
-
E.
laneCount
Indicates the number of parallel lanes associated with a given road or roadway segment.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48421c3048190b26864b72aad0d70 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.