Triple
T35636284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën C-Zero |
E1029728
|
entity |
| Predicate | electricRangeRealWorld |
P26736
|
FINISHED |
| Object | about 80–100 km |
—
|
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: about 80–100 km | Statement: [Citroën C-Zero, electricRangeRealWorld, about 80–100 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electricRangeRealWorld Context triple: [Citroën C-Zero, electricRangeRealWorld, about 80–100 km]
-
A.
electricRangeWLTP
Indicates the maximum distance a vehicle can travel on electric power alone according to the WLTP test cycle.
-
B.
electricRange
chosen
Indicates the maximum distance an electrically powered device or vehicle can travel or operate solely on electric power before needing to recharge.
-
C.
hasDrivingRange
Indicates that an entity (such as a vehicle or device) has a specific maximum distance it can travel or operate on a given amount of energy or fuel.
-
D.
energyUse
Indicates the amount or rate at which an entity consumes energy to perform its functions or activities.
-
E.
electricityUse
Indicates the amount or pattern of electrical energy consumed by an entity during a specified period or activity.
- 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_69f76e087bdc8190a4794bf9c0bd7634 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff53389a0481908b2baeb43c6294f0 |
completed | May 9, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69ff52e2b4b88190b38d160d771fe14b |
completed | May 9, 2026, 3:29 p.m. |
Created at: May 3, 2026, 4:05 p.m.