Triple
T8524188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Van Brienenoord Bridge |
E201769
|
entity |
| Predicate | hasLaneUsage |
P39910
|
FINISHED |
| Object | multiple traffic lanes in each direction |
—
|
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: multiple traffic lanes in each direction | Statement: [Van Brienenoord Bridge, hasLaneUsage, multiple traffic lanes in each direction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaneUsage Context triple: [Van Brienenoord Bridge, hasLaneUsage, multiple traffic lanes in each direction]
-
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.
canUseLaneConfiguration
Indicates that an entity is permitted or able to operate under a specified lane configuration.
-
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.
hasServiceLane
Indicates that a road or route includes an adjacent service lane intended for local or auxiliary traffic.
-
E.
hasTrackLanes
Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train movement.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe64362c88190b978a2544eec6e3e |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:16 p.m.