Triple

T8484220
Position Surface form Disambiguated ID Type / Status
Subject Charlie Brown E200792 entity
Predicate voiceActor P1507 FINISHED
Object Peter Robbins E736342 NE FINISHED

How this triple was built (2 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: Peter Robbins | Statement: [Charlie Brown, voiceActor, Peter Robbins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Robbins
Context triple: [Charlie Brown, voiceActor, Peter Robbins]
  • A. Peter Robbins chosen
    Peter Robbins was an American child actor best known as the original voice of Charlie Brown in the early Peanuts animated television specials.
  • B. Harry Robbins
    Harry Robbins "H. R." Haldeman was an American political aide who served as White House Chief of Staff to President Richard Nixon and became a central figure in the Watergate scandal.
  • C. Matthew Robbins
    Matthew Robbins is an American screenwriter and filmmaker known for his work on genre films such as Crimson Peak, Dragonslayer, and collaborations with directors like Guillermo del Toro.
  • D. Stephen Frank
    Stephen Frank was an early American pioneer after whom the city of Frankfort, Kentucky, is named.
  • E. Peter Hoffman
    Peter Hoffman is a relatively common personal name shared by multiple individuals across various professions, including arts, academia, and business.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca831d7b148190a6e32c1de43ab13b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe539b70c81909f8f045312f0d5f8 completed March 31, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4de95e3081908277c65598f3884a completed April 2, 2026, 11:07 a.m.
Created at: March 30, 2026, 6:12 p.m.