Triple

T6106222
Position Surface form Disambiguated ID Type / Status
Subject Rosa Diaz E136122 entity
Predicate createdBy P806 FINISHED
Object Michael Schur E129930 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: Michael Schur | Statement: [Rosa Diaz, createdBy, Michael Schur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Schur
Context triple: [Rosa Diaz, createdBy, Michael Schur]
  • A. Michael Schur chosen
    Michael Schur is an American television writer and producer best known for co-creating acclaimed comedy series such as Parks and Recreation, The Good Place, and Brooklyn Nine-Nine.
  • B. David Crane
    David Crane is an American television writer and producer best known for co-creating the hit sitcom "Friends."
  • C. David Crane
    David Crane is an American video game designer and programmer best known as a co-founder of Activision and creator of classic games like Pitfall!.
  • D. Nicholas Stoller
    Nicholas Stoller is a British-American filmmaker and screenwriter best known for directing and writing popular comedy films such as Forgetting Sarah Marshall and Neighbors.
  • E. Alec Berg
    Alec Berg is an American television writer, producer, and director known for his work on acclaimed comedy series such as Seinfeld, Curb Your Enthusiasm, and Silicon Valley.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b806bd48190b6f020af3391adb8 completed March 22, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1255759f48190a6aadf33406dcb49 completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:13 p.m.