Triple

T22996480
Position Surface form Disambiguated ID Type / Status
Subject Sugar Children E572207 entity
Predicate title P38 FINISHED
Object Sugar Children 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: Sugar Children | Statement: [Sugar Children, title, Sugar Children]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sugar Children
Context triple: [Sugar Children, title, Sugar Children]
  • A. Sugar Children chosen
    Sugar Children is a photographic series by Brazilian artist Vik Muniz in which he creates and documents portraits of Caribbean children using granulated sugar as his primary medium.
  • B. Sweet Children
    Sweet Children was the original name of the American punk rock band Green Day during their early years in the late 1980s.
  • C. For the Children
    "For the Children" is a studio album by British singer-songwriter and poet Labi Siffre, showcasing his introspective lyrics and soulful, folk-influenced sound.
  • D. Goodbye to Childhood
    "Goodbye to Childhood" is a song from the 1963 jazz album *Speak Like a Child* by trumpeter and composer Freddie Hubbard.
  • E. Everyone’s Child
    Everyone’s Child is a Zimbabwean drama film that portrays the struggles of orphaned siblings amid poverty and social upheaval.
  • 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_69e245b535808190adef8a9df3c584db completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182f3186c81909e0d5177029a72ae completed April 29, 2026, 4:02 a.m.
Created at: April 17, 2026, 3:50 p.m.