Triple

T22946469
Position Surface form Disambiguated ID Type / Status
Subject 10th Academy Awards E569886 entity
Predicate bestSongFilm P10680 FINISHED
Object Waikiki Wedding NE NERFINISHED

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: Waikiki Wedding | Statement: [10th Academy Awards, bestSongFilm, Waikiki Wedding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waikiki Wedding
Context triple: [10th Academy Awards, bestSongFilm, Waikiki Wedding]
  • A. Waikiki Wedding chosen
    Waikiki Wedding is a 1937 musical romantic comedy film starring Bing Crosby, set in Hawaii and known for its lighthearted plot and popular songs.
  • B. The Wedding Chapel
    The Wedding Chapel is a film featuring actor Christopher Candy in a notable role.
  • C. White Wedding
    "White Wedding" is a 1982 rock song by Billy Idol, known for its darkly romantic lyrics, distinctive guitar riff, and iconic MTV-era music video.
  • D. Wedding Day
    "Wedding Day" is a notable poem by Harlem Renaissance writer and artist Gwendolyn Bennett, reflecting her lyrical style and exploration of Black identity and emotional experience.
  • E. Wedding Day
    "Wedding Day" is a song by Tori Amos from her 2014 studio album *Unrepentant Geraldines*.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2459199d08190a8184ee2aa935842 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1819d2d7881909e6390717ff79df0 completed April 29, 2026, 3:57 a.m.
Created at: April 17, 2026, 3:46 p.m.