Triple

T22581517
Position Surface form Disambiguated ID Type / Status
Subject Mamma Roma E544578 entity
Predicate leadActressCharacterOccupation P125735 FINISHED
Object former prostitute LITERAL 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: former prostitute | Statement: [Mamma Roma, leadActressCharacterOccupation, former prostitute]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: leadActressCharacterOccupation
Context triple: [Mamma Roma, leadActressCharacterOccupation, former prostitute]
  • A. leadActress
    Indicates that the subject is the primary female performer in the specified film, show, or production.
  • B. occupationOfActress chosen
    Indicates that the specified occupation is the professional role held by a person who is an actress.
  • C. leadActorOccupation
    Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
  • D. portrayedByAlsoPlays
    Indicates that the actor who portrays a given character also plays another specified role or character.
  • E. directorCharacterOf
    Indicates that a director is responsible for directing a particular character in a work (e.g., film, TV show, or play).
  • F. None of above.

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_69e11e30d05481909df915354c89f0d6 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f15ff13e288190b5e4b527470be75e completed April 29, 2026, 1:33 a.m.
PD Predicate disambiguation batch_69ee626e6bb08190ada4dd8b48cc0c43 completed April 26, 2026, 7:07 p.m.
Created at: April 16, 2026, 8:53 p.m.