Triple

T6000867
Position Surface form Disambiguated ID Type / Status
Subject Kent State University E133591 entity
Predicate hasAcronym P43 FINISHED
Object 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.
 E560604 NE FINISHED

How this triple was built (4 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: [Kent State University, hasAcronym, KSU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KSU
Context triple: [Kent State University, hasAcronym, KSU]
  • A. KSU
    KSU is the vehicle registration code used for motor vehicles registered in Kristiansund, Norway.
  • B. KSU
    KSU is the vehicle registration code used on license plates for the town of Sucha Beskidzka in Poland.
  • C. 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.
  • D. KU
    KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
  • E. KU
    KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KSU
Triple: [Kent State University, hasAcronym, KSU]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KSU
Target entity description: 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.
  • A. KSU
    KSU is the vehicle registration code used on license plates for the town of Sucha Beskidzka in Poland.
  • B. KSU
    KSU is the vehicle registration code used for motor vehicles registered in Kristiansund, Norway.
  • C. 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.
  • D. KU
    KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
  • E. KU
    KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
  • F. None of above. chosen

Provenance (5 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_69c00872444c8190bfaf1739dcec765c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04ee7c0e08190a6e78969448b070a completed March 22, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1088366f08190bd65374d7a44fbc8 completed March 23, 2026, 9:31 a.m.
NEDg Description generation batch_69c1094d6d408190abde0d2e582c15a5 completed March 23, 2026, 9:35 a.m.
NED2 Entity disambiguation (via description) batch_69c109c333208190b90911e0cab58377 completed March 23, 2026, 9:37 a.m.
Created at: March 22, 2026, 4:05 p.m.