Triple
T2581717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tver Oblast |
E57105
|
entity |
| Predicate | hasVehicleCode |
P1173
|
FINISHED |
| Object | 69 |
—
|
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: 69 | Statement: [Tver Oblast, hasVehicleCode, 69]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleCode Context triple: [Tver Oblast, hasVehicleCode, 69]
-
A.
vehicleRegistrationCode
chosen
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
B.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
C.
hasPrimaryVehicularAccessTo
Indicates that one location or entity serves as the main route or means by which vehicles can reach or enter another location or entity.
-
D.
hasATCCode
Indicates that a pharmaceutical product or substance is assigned a specific Anatomical Therapeutic Chemical (ATC) classification code.
-
E.
hasINSEECODE
Indicates that an entity is associated with a specific INSEE code, identifying it within the French national statistical and administrative system.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c843bc8190837cea3441bf3ca1 |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.