Triple
T13613180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dam tram stop |
E325245
|
entity |
| Predicate | isInTrafficZone |
P110421
|
FINISHED |
| Object | Amsterdam city centre traffic-restricted area |
—
|
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: Amsterdam city centre traffic-restricted area | Statement: [Dam tram stop, isInTrafficZone, Amsterdam city centre traffic-restricted area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInTrafficZone Context triple: [Dam tram stop, isInTrafficZone, Amsterdam city centre traffic-restricted area]
-
A.
hasTrafficControl
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
B.
hasTrafficRegime
Indicates that a specified traffic control or regulatory system applies to a given road, area, or transport context.
-
C.
hasTrafficSignals
Indicates that traffic control signals are present at or associated with a given location or roadway feature.
-
D.
hasTrafficIsland
Indicates the presence of a traffic island separating or organizing lanes or directions of vehicular movement within a roadway.
-
E.
isTrafficCalmed
Indicates that a road or street has measures in place to reduce vehicle speed and improve safety for users.
- F. None of above. chosen
Provenance (4 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbbb8c77dc8190b7bd803b5e168d23 |
completed | April 12, 2026, 3:34 p.m. |
Created at: April 9, 2026, 9:50 p.m.