Triple

T6067058
Position Surface form Disambiguated ID Type / Status
Subject Bob's Burgers E135185 entity
Predicate voiceActor P1507 FINISHED
Object Dan Mintz
Dan Mintz is an American comedian, writer, and actor best known for voicing Tina Belcher on the animated television series "Bob's Burgers."
E565442 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 Mintz | Statement: [Bob's Burgers, voiceActor, Dan Mintz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Mintz
Context triple: [Bob's Burgers, voiceActor, Dan Mintz]
  • A. Dan Trachtenberg
    Dan Trachtenberg is an American filmmaker best known for directing the thriller "10 Cloverfield Lane" and the "Predator" prequel "Prey."
  • B. Mark Levine
    Mark Levine is an American politician and public servant who serves as the borough president of Manhattan in New York City.
  • C. Doug Mankoff
    Doug Mankoff is a film and television producer known for financing and executive producing a wide range of independent and prestige projects.
  • D. Greg Medavoy
    Greg Medavoy is a mild-mannered, often self-doubting detective whose personal growth and quiet competence provide both comic relief and emotional depth throughout the TV series "NYPD Blue."
  • E. Dan Mindel
    Dan Mindel is a British cinematographer known for his work on major blockbuster films, including entries in the Star Trek and Star Wars franchises.
  • 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 Mintz
Triple: [Bob's Burgers, voiceActor, Dan Mintz]
Generated description
Dan Mintz is an American comedian, writer, and actor best known for voicing Tina Belcher on the animated television series "Bob's Burgers."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dan Mintz
Target entity description: Dan Mintz is an American comedian, writer, and actor best known for voicing Tina Belcher on the animated television series "Bob's Burgers."
  • A. Dan Trachtenberg
    Dan Trachtenberg is an American filmmaker best known for directing the thriller "10 Cloverfield Lane" and the "Predator" prequel "Prey."
  • B. Mark Levine
    Mark Levine is an American politician and public servant who serves as the borough president of Manhattan in New York City.
  • C. Doug Mankoff
    Doug Mankoff is a film and television producer known for financing and executive producing a wide range of independent and prestige projects.
  • D. Greg Medavoy
    Greg Medavoy is a mild-mannered, often self-doubting detective whose personal growth and quiet competence provide both comic relief and emotional depth throughout the TV series "NYPD Blue."
  • E. Dan Mindel
    Dan Mindel is a British cinematographer known for his work on major blockbuster films, including entries in the Star Trek and Star Wars franchises.
  • 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_69c00879e8048190b690717d19c5bc03 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0573f17088190a728f1c290cc9d1d completed March 22, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d297ff88190a01b98f7ec9d9cf1 completed March 23, 2026, 10:59 a.m.
NEDg Description generation batch_69c11e956aa08190ac3fef49fb67471c completed March 23, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69c11f05ff9081908adc7f40fa12e834 completed March 23, 2026, 11:07 a.m.
Created at: March 22, 2026, 4:10 p.m.