Triple

T16256686
Position Surface form Disambiguated ID Type / Status
Subject Regierungsbezirk Mittelfranken E394647 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object SC E451097 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: SC | Statement: [Regierungsbezirk Mittelfranken, hasVehicleRegistrationCode, SC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SC
Context triple: [Regierungsbezirk Mittelfranken, hasVehicleRegistrationCode, SC]
  • A. SC
    SC is the standard two-letter postal abbreviation for the U.S. state of South Carolina.
  • B. SC chosen
    SC is the vehicle registration code used on license plates for the German town of Schwabach in Bavaria.
  • C. SC
    SC is the vehicle registration code used on license plates for vehicles registered in Częstochowa, a city in southern Poland.
  • D. SC
    SC is the commonly used abbreviation for Service Canada, the federal government agency that delivers a wide range of public services and benefits to Canadians.
  • E. SC
    SC is the official abbreviation used by the United States Navy to denote officers of its Supply Corps, the branch responsible for logistics, supply, and financial management.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2459b1624819086bf681075097235 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000eebcfe481909822290d3a7b361c completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:04 a.m.