Triple

T13347395
Position Surface form Disambiguated ID Type / Status
Subject Gmina Stryszawa E317987 entity
Predicate carPlatesCode P1173 FINISHED
Object KSU E81673 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: KSU | Statement: [Gmina Stryszawa, carPlatesCode, KSU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KSU
Context triple: [Gmina Stryszawa, carPlatesCode, KSU]
  • A. KSU
    KSU is the vehicle registration code used for motor vehicles registered in Kristiansund, Norway.
  • B. KSU
    KSU is a public research university in Kent, Ohio, known for its diverse academic programs and its historical significance related to the 1970 campus shootings.
  • C. KSU chosen
    KSU is the vehicle registration code used on license plates for the town of Sucha Beskidzka in Poland.
  • D. Kennesaw State University
    Kennesaw State University is a large public research university in Georgia known for its diverse academic programs and rapidly growing student population.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e89c65c819093f3bea11d6073c5 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f45c9788190b60095c0d6e2f763 completed May 3, 2026, 10:11 a.m.
Created at: April 9, 2026, 9:31 p.m.