Triple

T17423218
Position Surface form Disambiguated ID Type / Status
Subject Smokvica E423668 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object GE NE NERFINISHED

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: GE | Statement: [Smokvica, hasVehicleRegistrationCode, GE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GE
Context triple: [Smokvica, hasVehicleRegistrationCode, GE]
  • A. GE
    GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • B. GE chosen
    GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
  • C. GE
    GE is the abbreviation for ICANN’s Government Engagement function, which manages and coordinates ICANN’s relationships and interactions with governments and intergovernmental organizations worldwide.
  • D. GE
    GE is the commonly used abbreviation for Global Entry, a U.S. government program that provides expedited clearance for pre-approved, low-risk international travelers entering the United States.
  • E. GM
    GM is the station code used to identify GMA Kamuning station in the Manila Metro Rail Transit system.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44238b418819095c6a013d3ff3b17 completed April 19, 2026, 2:47 a.m.
Created at: April 10, 2026, 5:46 a.m.