Triple
T32390172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French departmental road network |
E827647
|
entity |
| Predicate | trafficMix |
P621
|
FINISHED |
| Object | light vehicles |
—
|
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: light vehicles | Statement: [French departmental road network, trafficMix, light vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficMix Context triple: [French departmental road network, trafficMix, light vehicles]
-
A.
trafficShare
Indicates the proportion of total traffic or visits that one entity receives relative to others within a defined context or time period.
-
B.
trafficType
chosen
Indicates the category or nature of traffic involved in a given interaction, flow, or connection (e.g., type of network, data, or transport traffic).
-
C.
trafficScope
Indicates the extent or range of traffic (e.g., network, road, or data flow) that is covered, affected, or governed by a given rule, condition, or entity.
-
D.
annualTraffic
Indicates the typical amount or volume of traffic associated with something over the course of a year.
-
E.
trafficFocus
Indicates a focus of attention or priority given to a particular traffic element, flow, or direction within a transportation or network context.
- 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_69f349184e7481909c6c54428cb9cf12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1d48d048190b6bb79e26881adb7 |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:52 a.m.