Triple

T11273009
Position Surface form Disambiguated ID Type / Status
Subject Cologne Government Region E266859 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object GM E745945 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: GM | Statement: [Cologne Government Region, hasVehicleRegistrationCode, GM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GM
Context triple: [Cologne Government Region, hasVehicleRegistrationCode, GM]
  • A. GM
    GM is the post-nominal abbreviation used to denote recipients of the George Medal, a British civilian decoration for bravery.
  • B. GM chosen
    GM is the vehicle registration code used on license plates for vehicles registered in the Oberbergischer Kreis district in North Rhine-Westphalia, Germany.
  • 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 ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • E. 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.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e965c9048190804ebb48f0a4817b completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f43633948190b86f5603ac50ec47 completed April 19, 2026, 3:26 p.m.
Created at: April 8, 2026, 9:31 p.m.