Triple

T14805713
Position Surface form Disambiguated ID Type / Status
Subject Linha de Passe E348028 entity
Predicate portraysCharacter P1668 FINISHED
Object Cleuza E1121317 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: Cleuza | Statement: [Linha de Passe, portraysCharacter, Cleuza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cleuza
Context triple: [Linha de Passe, portraysCharacter, Cleuza]
  • A. Cleuza chosen
    Cleuza is a central character in the Brazilian film "Linha de Passe," portrayed as a struggling single mother raising her sons in the outskirts of São Paulo.
  • B. Crateús
    Crateús is a municipality in the interior of the Brazilian state of Ceará, known as a regional commercial and service hub.
  • C. Ansião
    Ansião is a municipality in central Portugal known for its rural landscapes, historical churches, and traditional Portuguese architecture.
  • D. Jubiabá
    Jubiabá is a novel by Brazilian writer Jorge Amado that portrays Afro-Brazilian culture, social injustice, and popular resistance in Salvador, Bahia.
  • E. Melaque
    Melaque is a coastal town in Jalisco, Mexico, known for its relaxed beach atmosphere, tourism, and role as a popular vacation spot on the Pacific coast.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf32666081908e84f985c47eb963 completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe3893c760819094ce1d63478a39ce completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:34 a.m.