Triple

T37083
Position Surface form Disambiguated ID Type / Status
Subject United Kingdom E732 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object GB E732 NE 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: GB | Statement: [United Kingdom, vehicleRegistrationCode, GB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GB
Context triple: [United Kingdom, vehicleRegistrationCode, GB]
  • A. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • B. England
    England is a country within the United Kingdom, known for its rich history, cultural influence, and major cities such as London and Manchester.
  • C. BE
    BE is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Belgium in international standards and systems.
  • D. United Kingdom chosen
    The United Kingdom is a sovereign country in northwestern Europe comprising England, Scotland, Wales, and Northern Ireland, known for its parliamentary democracy, global cultural influence, and historic role in world affairs.
  • E. GAU
    GAU is an abbreviation commonly used for the University of Göttingen, a major research university in Göttingen, Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24acbb90881908c9f77e74034eb52 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a255322d048190b3a45c6c6a80230c completed Feb. 28, 2026, 2:38 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.