Triple

T2142847
Position Surface form Disambiguated ID Type / Status
Subject Toy Story 3 E46998 entity
Predicate voiceActor P1507 FINISHED
Object John Cygan
John Cygan was an American actor and voice actor known for his work in animated films, television, and video games.
 E242788 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: John Cygan | Statement: [Toy Story 3, voiceActor, John Cygan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Cygan
Context triple: [Toy Story 3, voiceActor, John Cygan]
  • A. Joe Pisarcik
    Joe Pisarcik is a former NFL quarterback best known for his infamous late-game fumble in 1978 that led to the "Miracle at the Meadowlands."
  • B. John Wolyniec
    John Wolyniec is a former American professional soccer forward best known for his time with the New York/New Jersey MetroStars and New York Red Bulls in Major League Soccer.
  • C. Mick Antoniw
    Mick Antoniw is a Welsh Labour politician and Member of the Senedd who has held senior legal and governmental roles in Wales.
  • D. Edward Ochab
    Edward Ochab was a Polish communist politician who briefly served as the de facto leader of Poland in 1956, overseeing the political transition during the Polish October reforms.
  • E. John Kundla
    John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
  • 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: John Cygan
Triple: [Toy Story 3, voiceActor, John Cygan]
Generated description
John Cygan was an American actor and voice actor known for his work in animated films, television, and video games.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Cygan
Target entity description: John Cygan was an American actor and voice actor known for his work in animated films, television, and video games.
  • A. Joe Pisarcik
    Joe Pisarcik is a former NFL quarterback best known for his infamous late-game fumble in 1978 that led to the "Miracle at the Meadowlands."
  • B. John Wolyniec
    John Wolyniec is a former American professional soccer forward best known for his time with the New York/New Jersey MetroStars and New York Red Bulls in Major League Soccer.
  • C. Mick Antoniw
    Mick Antoniw is a Welsh Labour politician and Member of the Senedd who has held senior legal and governmental roles in Wales.
  • D. Edward Ochab
    Edward Ochab was a Polish communist politician who briefly served as the de facto leader of Poland in 1956, overseeing the political transition during the Polish October reforms.
  • E. John Kundla
    John Kundla was a Hall of Fame American basketball coach best known for leading the Minneapolis Lakers to multiple early NBA championships.
  • 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_69a88a1933e0819094f18426ed74180f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe206db0819095772af5358dca55 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d92391c8190a11f96796507a8d3 completed March 9, 2026, 5:41 a.m.
NEDg Description generation batch_69ae5e5f023081909cd046b5850f8026 completed March 9, 2026, 5:45 a.m.
NED2 Entity disambiguation (via description) batch_69ae5ef99018819083a778378ea493e8 completed March 9, 2026, 5:47 a.m.
Created at: March 4, 2026, 7:44 p.m.