Triple

T6975650
Position Surface form Disambiguated ID Type / Status
Subject Arrival E161709 entity
Predicate producer P490 FINISHED
Object Dan Levine
Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
 E664621 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: Dan Levine | Statement: [Arrival, producer, Dan Levine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dan Levine
Context triple: [Arrival, producer, Dan Levine]
  • A. Nat Levine
    Nat Levine was an American film producer best known for founding Mascot Pictures and producing popular movie serials during the 1920s and 1930s.
  • B. Sam Levine
    Sam Levine is an American animation director and storyboard artist known for co-directing the superhero comedy film "DC League of Super-Pets."
  • C. Mitch Kertzman
    Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
  • D. Michael Greenberg
    Michael Greenberg is a prominent American neuroscientist renowned for his pioneering work on activity-dependent gene expression in the brain.
  • E. Sam Levy
    Sam Levy is an American cinematographer best known for his frequent collaborations with director Noah Baumbach and his work on acclaimed independent films.
  • 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: Dan Levine
Triple: [Arrival, producer, Dan Levine]
Generated description
Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dan Levine
Target entity description: Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
  • A. Nat Levine
    Nat Levine was an American film producer best known for founding Mascot Pictures and producing popular movie serials during the 1920s and 1930s.
  • B. Sam Levine
    Sam Levine is an American animation director and storyboard artist known for co-directing the superhero comedy film "DC League of Super-Pets."
  • C. Mitch Kertzman
    Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
  • D. Michael Greenberg
    Michael Greenberg is a prominent American neuroscientist renowned for his pioneering work on activity-dependent gene expression in the brain.
  • E. Sam Levy
    Sam Levy is an American cinematographer best known for his frequent collaborations with director Noah Baumbach and his work on acclaimed independent films.
  • 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_69c68854a0d88190bc0bf82263f1afce completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db3d3ab08190b107f3229c357dd2 completed March 27, 2026, 7:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8274d1994819089af156d634547ee completed March 28, 2026, 7:09 p.m.
NEDg Description generation batch_69c82833f394819092f24dbb35d9b25b completed March 28, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_69c82900c41481909f886fc565c57420 completed March 28, 2026, 7:16 p.m.
Created at: March 27, 2026, 2:31 p.m.