Triple

T2124340
Position Surface form Disambiguated ID Type / Status
Subject Toy Story E46393 entity
Predicate voiceActor P1507 FINISHED
Object Erik von Detten
Erik von Detten is an American actor best known for his work in popular 1990s and 2000s films and television series, including notable voice roles in animated features.
E236464 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: Erik von Detten | Statement: [Toy Story, voiceActor, Erik von Detten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erik von Detten
Context triple: [Toy Story, voiceActor, Erik von Detten]
  • A. Kyle Neptune
    Kyle Neptune is an American college basketball coach best known for leading the Villanova Wildcats men's basketball program.
  • B. Robby Mook
    Robby Mook is an American political strategist best known for serving as campaign manager for Hillary Clinton’s 2016 U.S. presidential campaign.
  • C. Luke Rowan
    Luke Rowan is a fictional character from the works of 19th-century English novelist Anthony Trollope.
  • D. Tobias Stansbury
    Tobias Stansbury was an American militia officer who led U.S. forces during the War of 1812’s Battle of Bladensburg, a key engagement preceding the British capture of Washington, D.C.
  • E. Craig Bierko
    Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
  • 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: Erik von Detten
Triple: [Toy Story, voiceActor, Erik von Detten]
Generated description
Erik von Detten is an American actor best known for his work in popular 1990s and 2000s films and television series, including notable voice roles in animated features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Erik von Detten
Target entity description: Erik von Detten is an American actor best known for his work in popular 1990s and 2000s films and television series, including notable voice roles in animated features.
  • A. Kyle Neptune
    Kyle Neptune is an American college basketball coach best known for leading the Villanova Wildcats men's basketball program.
  • B. Robby Mook
    Robby Mook is an American political strategist best known for serving as campaign manager for Hillary Clinton’s 2016 U.S. presidential campaign.
  • C. Luke Rowan
    Luke Rowan is a fictional character from the works of 19th-century English novelist Anthony Trollope.
  • D. Tobias Stansbury
    Tobias Stansbury was an American militia officer who led U.S. forces during the War of 1812’s Battle of Bladensburg, a key engagement preceding the British capture of Washington, D.C.
  • E. Craig Bierko
    Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb55cb2c8190aab8199da3335032 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae519bfdb08190a7b715fbc5fd3f41 completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae521c7810819086b88bb5f062597e completed March 9, 2026, 4:52 a.m.
NED2 Entity disambiguation (via description) batch_69ae52e79c788190bbe6eb5baba08a71 completed March 9, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:44 p.m.