Triple

T4237677
Position Surface form Disambiguated ID Type / Status
Subject University System of Georgia E94731 entity
Predicate hasPart P35 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: [University System of Georgia, hasPart, Kennesaw State University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kennesaw State University
Context triple: [University System of Georgia, hasPart, 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. Clayton State University
    Clayton State University is a public university in Morrow, Georgia, known for its diverse student body and career-focused academic programs.
  • 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_69b34537cc6481909cd0a96acbb33ef7 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e7589b48190a16e7ff29fb6a162 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a86996f48190987d3ac234a9b7f4 completed March 14, 2026, 6:26 p.m.
Created at: March 12, 2026, 11:05 p.m.