Triple
T2208329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French autoroute network |
E50854
|
entity |
| Predicate | typicalSpeedLimitUrbanSections |
P36051
|
FINISHED |
| Object | 90 km/h |
—
|
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: 90 km/h | Statement: [French autoroute network, typicalSpeedLimitUrbanSections, 90 km/h]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSpeedLimitUrbanSections Context triple: [French autoroute network, typicalSpeedLimitUrbanSections, 90 km/h]
-
A.
hasSpeedLimit
Indicates that a specified maximum allowable speed is imposed on the associated entity or context.
-
B.
hasSpeedLimitRange
Indicates that there is a specified minimum and maximum speed limit applicable to a given context or segment.
-
C.
hasSectionWithSpeedLimit
chosen
Indicates that an entity includes a segment or portion where a specific speed limit is in effect.
-
D.
trafficRestriction
Indicates a limitation or prohibition on the movement or flow of traffic between entities, such as vehicles, routes, or areas.
-
E.
isUrbanFreeway
Indicates that a roadway segment functions as a high-capacity, limited-access freeway located within an urban area.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.