Triple

T21450274
Position Surface form Disambiguated ID Type / Status
Subject A Thin Line Between Love and Hate E529188 entity
Predicate editedBy P1954 FINISHED
Object Michael Jablow NE NERFINISHED

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: Michael Jablow | Statement: [A Thin Line Between Love and Hate, editedBy, Michael Jablow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Jablow
Context triple: [A Thin Line Between Love and Hate, editedBy, Michael Jablow]
  • A. Michael Jablow chosen
    Michael Jablow is a film editor best known for his work on major Hollywood movies, including the baseball comedy-drama "A League of Their Own."
  • B. Michael Jaffe
    Michael Jaffe is an American television and film producer known for his work on numerous TV movies, series, and feature films.
  • C. Michael Skloff
    Michael Skloff is an American composer best known for co-writing and arranging the iconic theme song for the television series "Friends."
  • D. Michael Myerberg
    Michael Myerberg was an American theatrical producer and manager best known for his influential work on mid-20th-century Broadway productions.
  • E. Michael Haussman
    Michael Haussman is an American director and filmmaker best known for his work on high-profile music videos and commercials.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c457579481909db68053ed99750c completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d281c0819080c3f8a58947a115 completed April 23, 2026, 9:43 a.m.
Created at: April 16, 2026, 6:06 p.m.