Triple

T15731966
Position Surface form Disambiguated ID Type / Status
Subject The Mitchells vs. the Machines E381366 entity
Predicate cinematographyBy P1953 FINISHED
Object Mike Lasker
Mike Lasker is a visual effects supervisor and cinematographer known for his work on the animated film "The Mitchells vs. the Machines."
E1174489 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: Mike Lasker | Statement: [The Mitchells vs. the Machines, cinematographyBy, Mike Lasker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Lasker
Context triple: [The Mitchells vs. the Machines, cinematographyBy, Mike Lasker]
  • A. Alex Lasker
    Alex Lasker is a screenwriter best known for co-writing the military action film "Tears of the Sun."
  • B. Michael Brickler
    Michael Brickler is an entrepreneur best known as a co-founder of the architecture and design firm Morphosis.
  • C. Frank Palko
    Frank Palko was the criminal defendant at the center of the landmark U.S. Supreme Court case Palko v. Connecticut, which shaped the doctrine of selective incorporation of Bill of Rights protections to the states.
  • D. Milt Kushner
    Milt Kushner is an individual notable enough to be recognized as a prominent bearer of the surname Kushner.
  • E. Michael Peyser
    Michael Peyser is an American film and television producer known for his work on a variety of studio and independent projects.
  • 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: Mike Lasker
Triple: [The Mitchells vs. the Machines, cinematographyBy, Mike Lasker]
Generated description
Mike Lasker is a visual effects supervisor and cinematographer known for his work on the animated film "The Mitchells vs. the Machines."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mike Lasker
Target entity description: Mike Lasker is a visual effects supervisor and cinematographer known for his work on the animated film "The Mitchells vs. the Machines."
  • A. Alex Lasker
    Alex Lasker is a screenwriter best known for co-writing the military action film "Tears of the Sun."
  • B. Michael Brickler
    Michael Brickler is an entrepreneur best known as a co-founder of the architecture and design firm Morphosis.
  • C. Frank Palko
    Frank Palko was the criminal defendant at the center of the landmark U.S. Supreme Court case Palko v. Connecticut, which shaped the doctrine of selective incorporation of Bill of Rights protections to the states.
  • D. Milt Kushner
    Milt Kushner is an individual notable enough to be recognized as a prominent bearer of the surname Kushner.
  • E. Michael Peyser
    Michael Peyser is an American film and television producer known for his work on a variety of studio and independent projects.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd3614481908b2694b1d3550058 completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82fed7888190b45f28ac91e0079e completed May 9, 2026, 6:54 p.m.
NEDg Description generation batch_69ff83b7a534819090e24491579376c3 completed May 9, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_69ff844fa00c8190a47eb46394db097b completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:46 a.m.