Triple

T4622991
Position Surface form Disambiguated ID Type / Status
Subject Men in Black E101029 entity
Predicate editedBy P1954 FINISHED
Object Jim Miller
Jim Miller is a film editor known for his work on major Hollywood productions, including the science-fiction comedy "Men in Black."
 E456964 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: Jim Miller | Statement: [Men in Black, editedBy, Jim Miller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jim Miller
Context triple: [Men in Black, editedBy, Jim Miller]
  • A. Dan Miller
    Dan Miller is an American singer best known as a member of the early 2000s boy band O-Town formed on the reality TV show "Making the Band."
  • B. Ron Miller
    Ron Miller was an American film and television producer and former president and CEO of The Walt Disney Company, known for overseeing numerous Disney projects in the 1970s and 1980s.
  • C. Ron Miller
    Ron Miller is an American artist and illustrator renowned for his work in science fiction and astronomical art.
  • D. Ron Miller
    Ron Miller was an American songwriter best known for penning classic Motown hits, including the standard "For Once in My Life."
  • E. Jimmy Miller
    Jimmy Miller is a film and television producer best known for his work on hit comedies such as "Step Brothers" and other projects with major Hollywood comedians.
  • 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: Jim Miller
Triple: [Men in Black, editedBy, Jim Miller]
Generated description
Jim Miller is a film editor known for his work on major Hollywood productions, including the science-fiction comedy "Men in Black."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jim Miller
Target entity description: Jim Miller is a film editor known for his work on major Hollywood productions, including the science-fiction comedy "Men in Black."
  • A. Dan Miller
    Dan Miller is an American singer best known as a member of the early 2000s boy band O-Town formed on the reality TV show "Making the Band."
  • B. Ron Miller
    Ron Miller was an American film and television producer and former president and CEO of The Walt Disney Company, known for overseeing numerous Disney projects in the 1970s and 1980s.
  • C. Ron Miller
    Ron Miller is an American artist and illustrator renowned for his work in science fiction and astronomical art.
  • D. Ron Miller
    Ron Miller was an American songwriter best known for penning classic Motown hits, including the standard "For Once in My Life."
  • E. Jimmy Miller
    Jimmy Miller is a film and television producer best known for his work on hit comedies such as "Step Brothers" and other projects with major Hollywood comedians.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a053d38819097b3ecbc06aa6e4d completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaa069388190b6482315708b85c2 completed March 21, 2026, 1:55 a.m.
NEDg Description generation batch_69bdfb9422e48190819d5d99e72e8854 completed March 21, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_69bdfc6ac91c819090776365d3dc05d4 completed March 21, 2026, 2:03 a.m.
Created at: March 20, 2026, 1:12 p.m.