Triple

T20701176
Position Surface form Disambiguated ID Type / Status
Subject Tomorrowland E508785 entity
Predicate screenwriter P2831 FINISHED
Object Jeff Jensen
Jeff Jensen is an American writer and journalist best known in film for co-writing the science-fiction adventure movie "Tomorrowland."
 E1447771 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: Jeff Jensen | Statement: [Tomorrowland, screenwriter, Jeff Jensen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jeff Jensen
Context triple: [Tomorrowland, screenwriter, Jeff Jensen]
  • A. David Jensen
    David Jensen is a musician known for his work with the soft rock/R&B-influenced indie supergroup Gayngs.
  • B. Matthew Jensen
    Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
  • C. Bruce Jensen
    Bruce Jensen is an American illustrator best known for his distinctive science fiction book and magazine cover art.
  • D. Andrew Jorgenson
    Andrew Jorgenson is a principled, old-guard industrialist in the film "Other People’s Money," who fiercely defends his traditional manufacturing company against a ruthless corporate raider.
  • E. Ben F. Jensen
    Ben F. Jensen was a U.S. Congressman who was wounded during the 1954 shooting attack in the House of Representatives chamber.
  • 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: Jeff Jensen
Triple: [Tomorrowland, screenwriter, Jeff Jensen]
Generated description
Jeff Jensen is an American writer and journalist best known in film for co-writing the science-fiction adventure movie "Tomorrowland."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jeff Jensen
Target entity description: Jeff Jensen is an American writer and journalist best known in film for co-writing the science-fiction adventure movie "Tomorrowland."
  • A. David Jensen
    David Jensen is a musician known for his work with the soft rock/R&B-influenced indie supergroup Gayngs.
  • B. Matthew Jensen
    Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
  • C. Bruce Jensen
    Bruce Jensen is an American illustrator best known for his distinctive science fiction book and magazine cover art.
  • D. Andrew Jorgenson
    Andrew Jorgenson is a principled, old-guard industrialist in the film "Other People’s Money," who fiercely defends his traditional manufacturing company against a ruthless corporate raider.
  • E. Ben F. Jensen
    Ben F. Jensen was a U.S. Congressman who was wounded during the 1954 shooting attack in the House of Representatives chamber.
  • 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_69e0b4c2b2a481909e31e9cb8f81ab55 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6c18bfac08190bf80beeb3ce1951a completed April 21, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a08e82c317c8190b4947e8d32494074 completed May 16, 2026, 9:57 p.m.
NEDg Description generation batch_6a08e8aaf8c48190a39ff61647931670 completed May 16, 2026, 9:59 p.m.
NED2 Entity disambiguation (via description) batch_6a08e91102e081909b22c8d69c6c994c completed May 16, 2026, 10 p.m.
Created at: April 16, 2026, 12:12 p.m.