Triple
T19646967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doberman Pinscher |
E471698
|
entity |
| Predicate | legalStatusOfDocking |
P136813
|
FINISHED |
| Object | restricted or banned in many European countries |
—
|
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: restricted or banned in many European countries | Statement: [Doberman Pinscher, legalStatusOfDocking, restricted or banned in many European countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusOfDocking Context triple: [Doberman Pinscher, legalStatusOfDocking, restricted or banned in many European countries]
-
A.
hasDockingFacilities
Indicates that one entity provides or is equipped with docking facilities for another entity.
-
B.
parkingRequirement
Indicates the specified conditions or obligations related to providing or using parking associated with an entity or activity.
-
C.
hasParkingFor
Indicates that a place or facility provides designated parking spaces suitable for a specified type of vehicle or user.
-
D.
docking
Indicates the action of one vehicle or structure aligning and securely connecting to another for transfer, access, or support.
-
E.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64125dd9481908a891c71c975a964 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
| PDg | Predicate description generation | batch_69e51a23300c8190988552491d9783d7 |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 1:44 p.m.