Triple

T15372260
Position Surface form Disambiguated ID Type / Status
Subject parish of Walls and Flotta E367578 entity
Predicate civilParishFor P78401 FINISHED
Object Cava E1152473 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: Cava | Statement: [parish of Walls and Flotta, civilParishFor, Cava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cava
Context triple: [parish of Walls and Flotta, civilParishFor, Cava]
  • A. Cava chosen
    Cava is a small, sparsely populated island in the Orkney archipelago of Scotland, known for its rugged coastline and pastoral landscape.
  • B. Cava
    Cava is a fast-casual restaurant chain specializing in customizable Mediterranean-inspired bowls, pitas, and salads.
  • C. Cava DO
    Cava DO is a Spanish Denomination of Origin best known for its traditional-method sparkling wines produced primarily in Catalonia and other authorized regions of Spain.
  • D. Cava Baja
    Cava Baja is a famous, centuries-old street in Madrid’s historic center known for its traditional taverns, tapas bars, and vibrant nightlife.
  • E. Tarragona DO
    Tarragona DO is a Spanish Denominación de Origen wine region in Catalonia known for producing a range of red, white, and fortified wines influenced by its Mediterranean climate.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e5c1d548190930bfaf0861595ae completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13457418819088232270b092c969 completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:18 a.m.