Triple

T22582181
Position Surface form Disambiguated ID Type / Status
Subject Comédie-Italienne E544593 entity
Predicate typicalCharacterType P60013 FINISHED
Object Colombina 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: Colombina | Statement: [Comédie-Italienne, typicalCharacterType, Colombina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colombina
Context triple: [Comédie-Italienne, typicalCharacterType, Colombina]
  • A. Colombina chosen
    Colombina is a clever, flirtatious maid character from the Italian commedia dell’arte tradition, often portrayed as Harlequin’s witty and resourceful lover.
  • B. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • C. Rosana
    Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • D. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • E. Pelegrina
    Pelegrina is a small village in the municipality of Sigüenza, in the province of Guadalajara, Spain, known for its scenic setting near the Barranco del Río Dulce Natural Park.
  • 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_69e11e30d05481909df915354c89f0d6 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f15ff13e288190b5e4b527470be75e completed April 29, 2026, 1:33 a.m.
Created at: April 16, 2026, 8:53 p.m.