Triple

T3056729
Position Surface form Disambiguated ID Type / Status
Subject Ginny Newhart E60497 entity
Predicate relative P37 FINISHED
Object Bill Quinn
Bill Quinn was an American character actor known for his numerous supporting roles in film and television from the 1930s through the 1980s.
E356219 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: Bill Quinn | Statement: [Ginny Newhart, relative, Bill Quinn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Quinn
Context triple: [Ginny Newhart, relative, Bill Quinn]
  • A. Max Cullen
    Max Cullen is an Australian character actor known for his extensive work in film, television, and theatre over several decades.
  • B. Kevin Corcoran
    Kevin Corcoran was an American child actor best known for his roles in numerous Walt Disney films during the 1950s and 1960s.
  • C. David Sullivan
    David Sullivan is a British businessman and former pornography and media magnate best known as the co-owner and long-serving chairman of Premier League football club West Ham United.
  • D. Jim O’Brien
    Jim O’Brien is a former American football placekicker best known for kicking the game-winning field goal for the Baltimore Colts in Super Bowl V.
  • E. Phil Burke
    Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
  • 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: Bill Quinn
Triple: [Ginny Newhart, relative, Bill Quinn]
Generated description
Bill Quinn was an American character actor known for his numerous supporting roles in film and television from the 1930s through the 1980s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bill Quinn
Target entity description: Bill Quinn was an American character actor known for his numerous supporting roles in film and television from the 1930s through the 1980s.
  • A. Max Cullen
    Max Cullen is an Australian character actor known for his extensive work in film, television, and theatre over several decades.
  • B. Kevin Corcoran
    Kevin Corcoran was an American child actor best known for his roles in numerous Walt Disney films during the 1950s and 1960s.
  • C. David Sullivan
    David Sullivan is a British businessman and former pornography and media magnate best known as the co-owner and long-serving chairman of Premier League football club West Ham United.
  • D. Jim O’Brien
    Jim O’Brien is a former American football placekicker best known for kicking the game-winning field goal for the Baltimore Colts in Super Bowl V.
  • E. Phil Burke
    Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9bf7ebd48190ad5748a18fa9a56a completed March 8, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b354505574819083ae7d36e461366b completed March 13, 2026, 12:03 a.m.
NEDg Description generation batch_69b35546dfa0819081800009fbe8afe3 completed March 13, 2026, 12:07 a.m.
NED2 Entity disambiguation (via description) batch_69b355cecc4c81908ecb5f83e89b4a00 completed March 13, 2026, 12:09 a.m.
Created at: March 8, 2026, 3:02 p.m.