Triple

T12043074
Position Surface form Disambiguated ID Type / Status
Subject She Wants Me E286712 entity
Predicate writer P1360 FINISHED
Object Rob Margolies E961898 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: Rob Margolies | Statement: [She Wants Me, writer, Rob Margolies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rob Margolies
Context triple: [She Wants Me, writer, Rob Margolies]
  • A. Rob Margolies chosen
    Rob Margolies is an American film director, producer, and screenwriter known for his work on independent feature films and comedies.
  • B. Joe Mantello
    Joe Mantello is an acclaimed American actor and director, particularly renowned for his work on Broadway in both plays and musicals.
  • C. Lou Jacobi
    Lou Jacobi was a Canadian-born character actor known for his comedic roles in film, television, and theater, particularly in mid-20th-century Hollywood and Broadway productions.
  • D. Marty Grabstein
    Marty Grabstein is an American actor and voice actor best known for voicing the timid pink dog Courage in the animated series "Courage the Cowardly Dog."
  • E. Jim Jacobs
    Jim Jacobs was an American boxing manager and handball champion best known for managing heavyweight champion Mike Tyson during the early part of his professional career.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040d13108190bd1a969fa62aae5a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f649dbf081908e76c45e362217c1 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:47 p.m.