Triple

T16044530
Position Surface form Disambiguated ID Type / Status
Subject Lusia Strus E389181 entity
Predicate participatedIn P149 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: [Lusia Strus, participatedIn, 50 First Dates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 50 First Dates
Context triple: [Lusia Strus, participatedIn, 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1835d1dac819089abec9f0668ec78 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff29836bc8190b35f528d3e8547be completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 4:56 a.m.