Triple

T23331467
Position Surface form Disambiguated ID Type / Status
Subject La Latina E591454 entity
Predicate hasStreet P959 FINISHED
Object Cava Baja 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: Cava Baja | Statement: [La Latina, hasStreet, Cava Baja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cava Baja
Context triple: [La Latina, hasStreet, Cava Baja]
  • A. Cava Baja chosen
    Cava Baja is a famous, centuries-old street in Madrid’s historic center known for its traditional taverns, tapas bars, and vibrant nightlife.
  • B. La Cava
    La Cava is a surname most notably associated with American film director Gregory La Cava, known for his influential work in early 20th-century cinema.
  • C. Cava
    Cava is a small, sparsely populated island in the Orkney archipelago of Scotland, known for its rugged coastline and pastoral landscape.
  • D. Cava
    Cava is a fast-casual restaurant chain specializing in customizable Mediterranean-inspired bowls, pitas, and salads.
  • E. Capalonga
    Capalonga is a coastal municipality in the Philippine province of Camarines Norte known for its fishing communities, natural attractions, and religious pilgrimage sites.
  • 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_69e25d20156c81908c5c53195bd9c738 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197edfbbc81908cb56507cd280737 completed April 29, 2026, 5:32 a.m.
Created at: April 17, 2026, 5:15 p.m.