Triple

T21270545
Position Surface form Disambiguated ID Type / Status
Subject Mike Werb E524243 entity
Predicate hasWritingPartner P2389 FINISHED
Object Michael Colleary 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 Colleary | Statement: [Mike Werb, hasWritingPartner, Michael Colleary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Colleary
Context triple: [Mike Werb, hasWritingPartner, Michael Colleary]
  • A. Michael Colleary chosen
    Michael Colleary is an American screenwriter and producer best known for co-writing the action film "Face/Off" and working on various Hollywood genre movies and television projects.
  • B. Greg Colton
    Greg Colton is an American animation director best known for his work on the television series "Family Guy," including the acclaimed episode "Road to the Multiverse."
  • C. Michael Burke
    Michael Burke is a screenwriter best known for co-writing the film "Last Weekend."
  • D. Eric Millegan
    Eric Millegan is an American actor best known for playing Dr. Zack Addy on the television series "Bones."
  • E. Patrick Brice
    Patrick Brice is an American filmmaker and actor best known for directing and co-writing the indie horror film "Creep" and its sequel, as well as other offbeat, character-driven movies.
  • 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_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73651c9208190a87d45acd6fafaaa completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:01 p.m.