Triple

T13701140
Position Surface form Disambiguated ID Type / Status
Subject The Pest E328519 entity
Predicate director P255 FINISHED
Object Paul Miller
Paul Miller is a film director known for his work on the 1997 comedy movie "The Pest."
E1055693 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: Paul Miller | Statement: [The Pest, director, Paul Miller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Miller
Context triple: [The Pest, director, Paul Miller]
  • A. Carl Miller
    Carl Miller was an American silent film actor active in the 1920s, known for his supporting roles in several notable early Hollywood productions.
  • B. Peter Miller
    Peter Miller is a scholar known for his collaborative work with sociologist Nikolas Rose, particularly in the fields of governmentality, social theory, and the sociology of accounting and management.
  • C. Peter Miller
    Peter Miller is the central protagonist of the thriller film "Dressed to Kill," around whom the movie’s suspenseful plot and psychological tension revolve.
  • D. Neil Miller
    Neil Miller is a skeptical psychiatrist and the stepfather figure who provides comic tension and emotional contrast in the Christmas film "The Santa Clause."
  • E. 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."
  • 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: Paul Miller
Triple: [The Pest, director, Paul Miller]
Generated description
Paul Miller is a film director known for his work on the 1997 comedy movie "The Pest."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Paul Miller
Target entity description: Paul Miller is a film director known for his work on the 1997 comedy movie "The Pest."
  • A. Carl Miller
    Carl Miller was an American silent film actor active in the 1920s, known for his supporting roles in several notable early Hollywood productions.
  • B. Peter Miller
    Peter Miller is a scholar known for his collaborative work with sociologist Nikolas Rose, particularly in the fields of governmentality, social theory, and the sociology of accounting and management.
  • C. Peter Miller
    Peter Miller is the central protagonist of the thriller film "Dressed to Kill," around whom the movie’s suspenseful plot and psychological tension revolve.
  • D. Neil Miller
    Neil Miller is a skeptical psychiatrist and the stepfather figure who provides comic tension and emotional contrast in the Christmas film "The Santa Clause."
  • E. Dan Miller
    Dan Miller is a central character in the 2007 horror film "The Mist," known as a pragmatic and skeptical local who becomes a key figure in the tense human conflicts that arise when townspeople are trapped in a supermarket by a mysterious, deadly fog.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc879adc88190b03f1cf815b71061 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f794575d3881908de6ed988d848918 completed May 3, 2026, 6:30 p.m.
NEDg Description generation batch_69f79523bf608190addeca563bea132e completed May 3, 2026, 6:34 p.m.
NED2 Entity disambiguation (via description) batch_69f7965cc9f88190acbf232615a9e87b completed May 3, 2026, 6:39 p.m.
Created at: April 9, 2026, 9:54 p.m.