Triple

T15625589
Position Surface form Disambiguated ID Type / Status
Subject Mike and Dave Need Wedding Dates E375667 entity
Predicate producer P490 FINISHED
Object Peter Principato E889255 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: Peter Principato | Statement: [Mike and Dave Need Wedding Dates, producer, Peter Principato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Principato
Context triple: [Mike and Dave Need Wedding Dates, producer, Peter Principato]
  • A. Peter Principato chosen
    Peter Principato is a talent manager and television and film producer known for representing high-profile comedic actors and developing successful comedy projects.
  • B. Joe Principe
    Joe Principe is an American bassist best known as a founding member of the punk rock band Rise Against.
  • C. Frank Prinzi
    Frank Prinzi is an American cinematographer and television director known for his work on numerous films and TV series, including crime dramas and independent features.
  • D. Michael Prinz
    Michael Prinz is a person notable enough to be recognized as a prominent bearer of the surname Prinz.
  • E. Stephen Prina
    Stephen Prina is an American conceptual artist, musician, and educator known for his multidisciplinary works that critically engage with art history, music, and popular culture.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f415c2c81909e232e1c6531da93 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:14 a.m.