Triple

T4636323
Position Surface form Disambiguated ID Type / Status
Subject University of Idaho E101540 entity
Predicate president P8 FINISHED
Object Scott Green
Scott Green is an American higher-education administrator and business executive who serves as president of the University of Idaho.
 E458891 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: Scott Green | Statement: [University of Idaho, president, Scott Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Scott Green
Context triple: [University of Idaho, president, Scott Green]
  • A. Scott Green
    Scott Green is a former National Football League official best known for serving as a referee in multiple Super Bowls.
  • B. Jake Green
    Jake Green is the troubled professional gambler and ex-con protagonist of Guy Ritchie's 2005 crime thriller film "Revolver."
  • C. Bruce Green
    Bruce Green is a film editor known for his work on feature films including the 1995 drama "The Basketball Diaries."
  • D. Mark Greene
    Mark Greene is a central fictional emergency physician and one of the original main characters on the television series "ER."
  • E. Eric McLeod
    Eric McLeod is a film producer known for his work on major Hollywood action and genre movies, including the monster crossover blockbuster "Godzilla vs. Kong."
  • 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: Scott Green
Triple: [University of Idaho, president, Scott Green]
Generated description
Scott Green is an American higher-education administrator and business executive who serves as president of the University of Idaho.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Scott Green
Target entity description: Scott Green is an American higher-education administrator and business executive who serves as president of the University of Idaho.
  • A. Scott Green
    Scott Green is a former National Football League official best known for serving as a referee in multiple Super Bowls.
  • B. Jake Green
    Jake Green is the troubled professional gambler and ex-con protagonist of Guy Ritchie's 2005 crime thriller film "Revolver."
  • C. Bruce Green
    Bruce Green is a film editor known for his work on feature films including the 1995 drama "The Basketball Diaries."
  • D. Mark Greene
    Mark Greene is a central fictional emergency physician and one of the original main characters on the television series "ER."
  • E. Eric McLeod
    Eric McLeod is a film producer known for his work on major Hollywood action and genre movies, including the monster crossover blockbuster "Godzilla vs. Kong."
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a60a66c8190b76f3d3a7da1df55 completed March 20, 2026, 2:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfacba5fc8190bc86157ee5719ced completed March 21, 2026, 1:56 a.m.
NEDg Description generation batch_69bdfed8a8b48190bcb98e2ff1886b65 completed March 21, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_69bdff9ff3748190af5e5a6d91976abc completed March 21, 2026, 2:17 a.m.
Created at: March 20, 2026, 1:13 p.m.