Triple

T24525795
Position Surface form Disambiguated ID Type / Status
Subject NDSU Extension Service E606661 entity
Predicate usesKnowledgeBase P156611 FINISHED
Object research from North Dakota State University LITERAL 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: research from North Dakota State University | Statement: [NDSU Extension Service, usesKnowledgeBase, research from North Dakota State University]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesKnowledgeBase
Context triple: [NDSU Extension Service, usesKnowledgeBase, research from North Dakota State University]
  • A. usesKnowledgeOf
    Indicates that one entity applies or draws upon the knowledge possessed by another entity in performing an action or achieving a result.
  • B. knows
    Indicates that one entity has knowledge or awareness of another entity or piece of information.
  • C. haveKnowledgeSystem
    Indicates that an entity possesses or maintains a structured system for organizing, storing, and accessing knowledge.
  • D. knowledgeOutput
    Indicates that an entity produces, expresses, or makes available knowledge, information, or learned content as an output.
  • E. knowledgeType
    Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
  • F. None of above. chosen

Provenance (4 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_69e2c4c85778819085f5da9af3569ad5 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2be044d4c819094e14eda28d371a7 completed April 30, 2026, 2:27 a.m.
PD Predicate disambiguation batch_69f2a6b0ca8081908d931aec560eae56 completed April 30, 2026, 12:47 a.m.
PDg Predicate description generation batch_69f2b8b8bc5881908df49c0b07110246 completed April 30, 2026, 2:04 a.m.
Created at: April 18, 2026, 2:25 a.m.