Triple
T35743090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BR-43 |
E1033093
|
entity |
| Predicate | countryCodeOnPlates |
P192754
|
FINISHED |
| Object | IND |
—
|
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: IND | Statement: [BR-43, countryCodeOnPlates, IND]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCodeOnPlates Context triple: [BR-43, countryCodeOnPlates, IND]
-
A.
licensePlateOrigin
Indicates that a vehicle’s license plate was issued or originates from a particular jurisdiction or region.
-
B.
countryVehicleRegistrationSystem
Indicates a relationship where a country maintains or governs an official system for registering vehicles within its jurisdiction.
-
C.
registrationPlateFormat
Indicates the specific pattern or structure that a vehicle’s registration plate must follow (such as the arrangement of letters, numbers, and symbols).
-
D.
usesCodeOnPlates
Indicates that an entity applies or employs a specific code or coding system on plates.
-
E.
countryDenoted
chosen
Indicates that one entity is a name, code, or symbol that specifically refers to or designates a particular country.
- 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a01f4d954e08190aff3756955212d67 |
completed | May 11, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_6a01edadb9248190be592287530740a5 |
completed | May 11, 2026, 2:54 p.m. |
Created at: May 3, 2026, 4:06 p.m.