Triple

T22102445
Position Surface form Disambiguated ID Type / Status
Subject Joy (2015 film) E546203 entity
Predicate mainCharacter P1183 FINISHED
Object Joy Mangano 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: Joy Mangano | Statement: [Joy (2015 film), mainCharacter, Joy Mangano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joy Mangano
Context triple: [Joy (2015 film), mainCharacter, Joy Mangano]
  • A. Joy Mangano chosen
    Joy Mangano is an American inventor and entrepreneur best known for creating the Miracle Mop and for her appearances on the Home Shopping Network.
  • B. Judy Luciano
    Judy Luciano is known for being married to American actor and comedian Don Adams, famed for his role in the television series "Get Smart."
  • C. Roberta Rigano
    Roberta Rigano is an actress known for her role in the romantic drama miniseries "From Scratch."
  • D. Barbara Mastroianni
    Barbara Mastroianni is an Italian costume designer and the daughter of renowned actor Marcello Mastroianni.
  • E. Mary Rotolo
    Mary Rotolo was the mother of artist and activist Suze Rotolo, who was closely associated with Bob Dylan and the 1960s Greenwich Village folk scene.
  • 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_69e11e378dc08190896d6a51597afd5a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129163b908190b63ace06016f4db8 completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.