Triple

T10390975
Position Surface form Disambiguated ID Type / Status
Subject Ron’s Gone Wrong E244889 entity
Predicate voiceCastMember P9616 FINISHED
Object Marcus Scribner E778995 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: Marcus Scribner | Statement: [Ron’s Gone Wrong, voiceCastMember, Marcus Scribner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marcus Scribner
Context triple: [Ron’s Gone Wrong, voiceCastMember, Marcus Scribner]
  • A. Marcus Scribner chosen
    Marcus Scribner is an American actor best known for playing Andre Johnson Jr. on the ABC sitcom "Black-ish."
  • B. Alex Reiger
    Alex Reiger is the level-headed, philosophical cab driver who serves as the central character in the classic television sitcom "Taxi."
  • C. Charlie Corwin
    Charlie Corwin is an American television and film producer and media executive known for developing and overseeing a wide range of unscripted and scripted entertainment projects.
  • D. Orator Shafer
    Orator Shafer was a 19th-century American professional baseball outfielder known for his strong throwing arm and standout defensive play.
  • E. Alex Datcher
    Alex Datcher is an American actress best known for her role as a flight attendant alongside Wesley Snipes in the 1992 action film "Passenger 57."
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b4f7d08190bcb16d3b4c8f22ad completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f6fbc848190806d50bfad654b27 completed April 10, 2026, 6:57 a.m.
Created at: April 6, 2026, 12:06 p.m.