Triple
T18156480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nouvelle Chicane |
E434643
|
entity |
| Predicate | hasBrakingZoneFrom |
P130668
|
FINISHED |
| Object | high speed |
—
|
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 speed | Statement: [Nouvelle Chicane, hasBrakingZoneFrom, high speed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrakingZoneFrom Context triple: [Nouvelle Chicane, hasBrakingZoneFrom, high speed]
-
A.
hasBraking
Indicates that an entity possesses or is equipped with a braking capability or braking system.
-
B.
hasPedestrianZoneStatus
Indicates whether an area or segment is designated as a pedestrian-only or pedestrian-priority zone and its corresponding status.
-
C.
isInTrafficZone
Indicates that an entity is located within a designated traffic-regulated area or zone.
-
D.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
-
E.
hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debe27a88190bd76c6f78fcf1bd1 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:30 a.m.