Triple
T13984609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coulée verte cycle path |
E336404
|
entity |
| Predicate | trafficFree |
P63213
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Coulée verte cycle path, trafficFree, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficFree Context triple: [Coulée verte cycle path, trafficFree, true]
-
A.
isCarFreeAtTimes
Indicates that an entity is free of cars or motor vehicles during certain specified times or periods.
-
B.
carFree
chosen
Indicates that an area, route, or zone is designated for use without cars or motor vehicles.
-
C.
trafficLevel
Indicates the degree of congestion or flow intensity present in a transportation network or route at a given time.
-
D.
relievesTrafficFrom
Indicates that one entity reduces or alleviates traffic congestion that would otherwise occur on another entity.
-
E.
traffics
Indicates engaging in the buying, selling, or illicit trading of someone or something, typically as part of an ongoing commercial or criminal operation.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea3e5a081908ed8ead108139252 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.