Triple

T21116781
Position Surface form Disambiguated ID Type / Status
Subject Yes Man (film) E520319 entity
Predicate screenwriter P2831 FINISHED
Object Andrew Mogel 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: Andrew Mogel | Statement: [Yes Man (film), screenwriter, Andrew Mogel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andrew Mogel
Context triple: [Yes Man (film), screenwriter, Andrew Mogel]
  • A. Andrew Mogel chosen
    Andrew Mogel is a television writer and producer best known for co-creating the sitcom "The Grinder."
  • B. Jake Morgendorffer
    Jake Morgendorffer is the neurotic, well-meaning but often clueless father of Daria Morgendorffer in the animated TV series "Daria."
  • C. Anthony Seigler
    Anthony Seigler is an American professional baseball catcher who was a first-round draft pick of the New York Yankees.
  • D. Anthony Meyer
    Anthony Meyer is a British politician and former Conservative Member of Parliament best known for mounting a symbolic leadership challenge against Prime Minister Margaret Thatcher in 1989.
  • E. Andrew Braunsberg
    Andrew Braunsberg is a film producer best known for his work on the acclaimed 1979 satirical comedy-drama "Being There."
  • 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72106a3b48190a0efa51a74ae21f0 completed April 21, 2026, 7:02 a.m.
Created at: April 16, 2026, 2:55 p.m.