Triple

T16073113
Position Surface form Disambiguated ID Type / Status
Subject Jason Friedberg E389913 entity
Predicate notableWork P4 FINISHED
Object Date Movie E1156807 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: Date Movie | Statement: [Jason Friedberg, notableWork, Date Movie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Date Movie
Context triple: [Jason Friedberg, notableWork, Date Movie]
  • A. Date Movie chosen
    Date Movie is a 2006 parody film that satirizes popular romantic comedies through broad slapstick and pop-culture references.
  • B. The Movies
    The Movies is a simulation video game that lets players run a Hollywood film studio, managing production, stars, and the creation of custom movies.
  • C. YTS
    YTS is the IATA airport code for Timmins Victor M. Power Airport, a regional airport serving the city of Timmins in Ontario, Canada.
  • D. At the Movies
    At the Movies was an Australian film review television program best known for its long-running co-hosts Margaret Pomeranz and David Stratton, who offered in-depth critiques and discussions of new cinema releases.
  • E. At the Movies
    At the Movies was a long-running American film review television program, best known for featuring critics like Roger Ebert who popularized the "thumbs up/thumbs down" style of movie criticism.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183bf6c488190b0099a00f13f2a69 completed April 17, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb8f12708190956f203a3e58e18b completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 4:57 a.m.