Triple

T10441833
Position Surface form Disambiguated ID Type / Status
Subject Rachel Bay Jones E246187 entity
Predicate performedIn P795 FINISHED
Object Hair E267551 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: Hair | Statement: [Rachel Bay Jones, performedIn, Hair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hair
Context triple: [Rachel Bay Jones, performedIn, Hair]
  • A. Hair chosen
    Hair is a 1979 musical anti-war film directed by Miloš Forman, adapted from the 1960s stage musical and known for its portrayal of the hippie counterculture and Vietnam War–era America.
  • B. How To (Hair)
    "How To (Hair)" is a track from Esperanza Spalding’s experimental jazz album *12 Little Spells*, which blends innovative composition with conceptual, body-themed song titles.
  • C. Hair Body Face
    "Hair Body Face" is a pop song performed by Lady Gaga from the soundtrack of the 2018 film *A Star Is Born*.
  • D. The Hair Buyer
    The Hair Buyer is a character from the musical "Hamilton," known for purchasing Eliza Hamilton’s hair in the song "Burn."
  • E. Bangs
    Bangs is a surname of English origin borne by various notable individuals, including scientists, writers, and public figures.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fb9ebf488190ae776bd65e94cb00 completed April 7, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87ed6edd88190afd5063daba58a46 completed April 10, 2026, 4:38 a.m.
Created at: April 6, 2026, 12:15 p.m.