Triple

T20278150
Position Surface form Disambiguated ID Type / Status
Subject Commedia dell’arte E503067 entity
Predicate hasStockCharacter P139519 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: [Commedia dell’arte, hasStockCharacter, Colombina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colombina
Context triple: [Commedia dell’arte, hasStockCharacter, 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 Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • C. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e59f7c819086638b871ecbbd40 completed April 20, 2026, 6:52 p.m.
Created at: April 16, 2026, 10:35 a.m.