Triple

T8770908
Position Surface form Disambiguated ID Type / Status
Subject Drew Barrymore E208457 entity
Predicate notableWork P4 FINISHED
Object 50 First Dates E91633 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: 50 First Dates | Statement: [Drew Barrymore, notableWork, 50 First Dates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 50 First Dates
Context triple: [Drew Barrymore, notableWork, 50 First Dates]
  • A. 50 First Dates chosen
    50 First Dates is a 2004 romantic comedy film starring Adam Sandler and Drew Barrymore about a man who repeatedly courts a woman with short-term memory loss.
  • B. First Date
    "First Date" is a popular pop-punk song by American rock band Blink-182, known for its catchy melody and humorous take on the awkwardness of teenage romance.
  • C. Sleepless in Seattle
    Sleepless in Seattle is a 1993 romantic comedy-drama film starring Tom Hanks and Meg Ryan, centered on a widower whose son calls a radio show to help find him a new partner.
  • D. The Wedding Singer
    The Wedding Singer is a Broadway musical comedy, based on the 1998 Adam Sandler film, that follows a jilted 1980s wedding singer who finds unexpected love.
  • E. The Wedding Date
    The Wedding Date is a 2005 romantic comedy film in which a woman hires a charming male escort to pose as her boyfriend at her sister’s wedding, leading to unexpected romance and complications.
  • 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_69ca835edb4481909b4aafb616dc5eb7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f2b08f881909f3d4fab2eda1d67 completed March 31, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51b7d05c8190b84e02a8796d3422 completed April 3, 2026, 5:35 a.m.
Created at: March 30, 2026, 6:41 p.m.