Triple

T8515669
Position Surface form Disambiguated ID Type / Status
Subject Joey King E201565 entity
Predicate notableWork P4 FINISHED
Object The Kissing Booth 2 E733178 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: The Kissing Booth 2 | Statement: [Joey King, notableWork, The Kissing Booth 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Kissing Booth 2
Context triple: [Joey King, notableWork, The Kissing Booth 2]
  • A. The Kissing Booth chosen
    The Kissing Booth is a 2018 Netflix teen romantic comedy film about a high school girl whose life is complicated when she falls for her best friend's older brother.
  • B. Kissing Lessons
    "Kissing Lessons" is an indie rock song by American singer-songwriter Lucy Dacus, known for its nostalgic storytelling and intimate, coming-of-age themes.
  • C. The Perfect Kiss
    "The Perfect Kiss" is a 1985 synth-pop and post-punk track by English band New Order, known for its extended 12" version, innovative production, and iconic Jonathan Demme–directed music video.
  • D. The Price of Kissing
    The Price of Kissing is a 1997 independent romantic drama film featuring Pauley Perrette in one of her early screen roles.
  • E. 50 First Kisses
    50 First Kisses is a Japanese romantic comedy film that remakes and localizes the story of the American movie "50 First Dates" for a Japanese audience.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60f37b0819082ae14e539f57b56 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d37df3081909d8d38363b8d2304 completed April 2, 2026, 1:20 p.m.
Created at: March 30, 2026, 6:15 p.m.