Triple

T13323347
Position Surface form Disambiguated ID Type / Status
Subject Bad Ems E317369 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object EMS E626283 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: EMS | Statement: [Bad Ems, vehicleRegistrationCode, EMS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EMS
Context triple: [Bad Ems, vehicleRegistrationCode, EMS]
  • A. EMS
    EMS is an emergency medical services organization that provides pre-hospital care and ambulance transport in response to medical emergencies.
  • B. EMS chosen
    EMS is the vehicle registration code used on license plates for vehicles registered in the district of Rhein-Lahn-Kreis, whose administrative seat is Nassau, in the German state of Rhineland-Palatinate.
  • C. EMS
    EMS is a Christian mission organization focused on international partnership, evangelism, and social justice work, particularly within the global evangelical community.
  • D. EMS
    EMS (Enhanced Messaging Service) is a mobile messaging standard that extends basic SMS by allowing the exchange of simple multimedia content such as formatted text, icons, animations, and ringtones between compatible phones.
  • E. Ems Dispatch
    The Ems Dispatch was a deliberately edited telegram from King Wilhelm I of Prussia whose publication in 1870 inflamed Franco-Prussian tensions and helped trigger the Franco-Prussian War.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992c1fec8190bcb6a6bb3c973a24 completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f2cd5688190a2a0db0f0295de83 completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 9:30 p.m.