Triple

T9004989
Position Surface form Disambiguated ID Type / Status
Subject Kufstein E215120 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object KU E230930 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: KU | Statement: [Kufstein, vehicleRegistrationCode, KU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KU
Context triple: [Kufstein, vehicleRegistrationCode, KU]
  • A. KU
    KU is the commonly used abbreviation for Kettering University, a private university in Flint, Michigan known for its strong engineering and cooperative education programs.
  • B. KU chosen
    KU is the vehicle registration code assigned to the district of Kulmbach in the Upper Franconia region of Bavaria, Germany.
  • C. KU
    KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
  • D. KU
    KU is the University of Kansas, a major public research university in Lawrence, Kansas, known for its strong athletics and distinctive school traditions.
  • E. KU
    KU is the commonly used abbreviation for Kutztown University of Pennsylvania, a public university located in Kutztown, Pennsylvania.
  • 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_69ca83a12d648190b1e4fe11e8a31890 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc695afa34819086cf6fcce2997b5f completed April 1, 2026, 12:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0e3f0c88190ae688632be25e5c9 completed April 3, 2026, 2:38 p.m.
Created at: March 30, 2026, 7:05 p.m.