Triple

T5188723
Position Surface form Disambiguated ID Type / Status
Subject Poetry: A Magazine of Verse E117095 entity
Predicate editor P1954 FINISHED
Object Don Share
Don Share is an American poet, translator, and literary editor best known for his tenure as editor of the influential journal Poetry magazine.
 E502168 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: Don Share | Statement: [Poetry: A Magazine of Verse, editor, Don Share]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Don Share
Context triple: [Poetry: A Magazine of Verse, editor, Don Share]
  • A. Ron Torbert
    Ron Torbert is an American NFL official who has served as a referee in multiple high-profile games, including Super Bowl LVI.
  • B. Dennis Shaw
    Dennis Shaw is a former American football quarterback who starred at San Diego State before playing in the NFL, most notably for the Buffalo Bills.
  • C. Ed Vargo
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • D. Dick Hantak
    Dick Hantak is a former National Football League official best known for serving as the referee in Super Bowl XXVII.
  • E. Dan Rydell
    Dan Rydell is a charismatic, quick-witted sports anchor and one of the central protagonists on the television series "Sports Night."
  • 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: Don Share
Triple: [Poetry: A Magazine of Verse, editor, Don Share]
Generated description
Don Share is an American poet, translator, and literary editor best known for his tenure as editor of the influential journal Poetry magazine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Don Share
Target entity description: Don Share is an American poet, translator, and literary editor best known for his tenure as editor of the influential journal Poetry magazine.
  • A. Ron Torbert
    Ron Torbert is an American NFL official who has served as a referee in multiple high-profile games, including Super Bowl LVI.
  • B. Dennis Shaw
    Dennis Shaw is a former American football quarterback who starred at San Diego State before playing in the NFL, most notably for the Buffalo Bills.
  • C. Ed Vargo
    Ed Vargo was a prominent Major League Baseball umpire who worked in the National League for over two decades and officiated multiple World Series and All-Star Games.
  • D. Dick Hantak
    Dick Hantak is a former National Football League official best known for serving as the referee in Super Bowl XXVII.
  • E. Dan Rydell
    Dan Rydell is a charismatic, quick-witted sports anchor and one of the central protagonists on the television series "Sports Night."
  • 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_69bd44620ff48190bcac01782107a397 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79c732b48190af62dfffcbc5e3a6 completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee08af954819080dbe7ea1ac6ddb0 completed March 21, 2026, 6:16 p.m.
NEDg Description generation batch_69bee5fc0c408190b4ad4b77e0045182 completed March 21, 2026, 6:39 p.m.
NED2 Entity disambiguation (via description) batch_69bee6b954c08190a353ebcfe829888a completed March 21, 2026, 6:43 p.m.
Created at: March 20, 2026, 1:46 p.m.