Triple

T12277472
Position Surface form Disambiguated ID Type / Status
Subject Buddy Hobbs E292626 entity
Predicate portrayedBy P1507 FINISHED
Object Will Ferrell E12114 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: Will Ferrell | Statement: [Buddy Hobbs, portrayedBy, Will Ferrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Will Ferrell
Context triple: [Buddy Hobbs, portrayedBy, Will Ferrell]
  • A. Will Ferrell chosen
    Will Ferrell is an American comedian, actor, writer, and producer best known for his work on "Saturday Night Live" and a series of hit comedy films such as "Anchorman" and "Elf."
  • B. Will Forte
    Will Forte is an American actor, comedian, and writer best known for his work on "Saturday Night Live" and for creating and starring in the TV series "The Last Man on Earth."
  • C. Jon Heder
    Jon Heder is an American actor best known for his breakout role in the cult comedy film "Napoleon Dynamite" and subsequent performances in various comedy movies.
  • D. Owen Wilson
    Owen Wilson is an American actor and screenwriter known for his laid-back charm and roles in popular comedies and adventure films such as "Wedding Crashers," "Zoolander," and "Midnight in Paris."
  • E. Luke Wilson
    Luke Wilson is an American actor known for his roles in films such as "The Royal Tenenbaums," "Old School," and "Legally Blonde."
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf06cf08190ac8671dd9bbed03d completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e6d72d081908c8697257df712f1 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:52 p.m.