Triple
T35669570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 110 in Los Angeles |
E1030672
|
entity |
| Predicate | hasLanesType |
P39910
|
FINISHED |
| Object | high-occupancy vehicle 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: high-occupancy vehicle lanes | Statement: [Interstate 110 in Los Angeles, hasLanesType, high-occupancy vehicle lanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanesType Context triple: [Interstate 110 in Los Angeles, hasLanesType, high-occupancy vehicle lanes]
-
A.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
B.
hasTrackLanes
Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train movement.
-
C.
hasLaneConfigurations
chosen
Indicates that an entity is associated with one or more specific arrangements or patterns of lanes (e.g., number, type, or direction of lanes).
-
D.
hasDedicatedLanes
Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
-
E.
hasSecurityLanes
Indicates that an entity is equipped with designated security screening lanes for processing people or items.
- 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
Created at: May 3, 2026, 4:05 p.m.