Triple

T13941421
Position Surface form Disambiguated ID Type / Status
Subject Peter Segal E335261 entity
Predicate directed P7373 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: [Peter Segal, directed, 50 First Dates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 50 First Dates
Context triple: [Peter Segal, directed, 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2cf6e29881908ddb8efca9a456a3 completed April 14, 2026, 12:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1ca49a881909e77b5a2ae13265f completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:17 p.m.