Triple

T17418796
Position Surface form Disambiguated ID Type / Status
Subject Nottuln E423554 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object COE 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: COE | Statement: [Nottuln, vehicleRegistrationCode, COE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: COE
Context triple: [Nottuln, vehicleRegistrationCode, COE]
  • A. COE
    COE is the Spanish National Olympic Committee responsible for organizing Spain’s participation in the Olympic Games and promoting the Olympic movement within the country.
  • B. COE chosen
    COE is the vehicle registration code used on license plates for the Coesfeld district in the German state of North Rhine-Westphalia.
  • C. CoE
    CoE is the commonly used abbreviation for the Council of Europe, a pan-European intergovernmental organization focused on promoting human rights, democracy, and the rule of law.
  • D. CoE
    CoE is the commonly used abbreviation for the Centers of Excellence within the Technology Transformation Services (TTS) of the U.S. General Services Administration.
  • E. CCoE
    CCoE is the U.S. Army’s primary institution responsible for developing doctrine, training, and capabilities for cyber and electronic warfare operations.
  • 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44234d840819096484a15d407785a completed April 19, 2026, 2:47 a.m.
Created at: April 10, 2026, 5:46 a.m.