Triple

T7319538
Position Surface form Disambiguated ID Type / Status
Subject Kennesaw, Georgia E168502 entity
Predicate hasInstitution P186 FINISHED
Object Kennesaw State University E370944 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: Kennesaw State University | Statement: [Kennesaw, Georgia, hasInstitution, Kennesaw State University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kennesaw State University
Context triple: [Kennesaw, Georgia, hasInstitution, Kennesaw State University]
  • A. Kennesaw State University chosen
    Kennesaw State University is a large public research university in Georgia known for its diverse academic programs and rapidly growing student population.
  • B. Georgia State University
    Georgia State University is a large public research university known for its diverse student body and urban campus in downtown Atlanta, Georgia.
  • C. KSU
    KSU is the vehicle registration code used for motor vehicles registered in Kristiansund, Norway.
  • D. KSU
    KSU is the vehicle registration code used on license plates for the town of Sucha Beskidzka in Poland.
  • E. 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.
  • 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ef1a7a3c81909504eb711056f302 completed March 27, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eefcd7148190818d581cbde9aff1 completed March 28, 2026, 3:08 p.m.
Created at: March 27, 2026, 3:02 p.m.