Triple

T20163838
Position Surface form Disambiguated ID Type / Status
Subject PortAventura Park E491779 entity
Predicate locatedIn P40 FINISHED
Object Vila-seca 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: Vila-seca | Statement: [PortAventura Park, locatedIn, Vila-seca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila-seca
Context triple: [PortAventura Park, locatedIn, Vila-seca]
  • A. Vila-seca chosen
    Vila-seca is a coastal municipality in Catalonia, Spain, known for its tourism, proximity to Tarragona, and educational facilities including a campus of Rovira i Virgili University.
  • B. Afogados
    Afogados is a populous neighborhood in the Brazilian city of Recife, known for its busy commercial areas and dense urban character.
  • C. Cabaceiras
    Cabaceiras is a historic town in the Brazilian state of Paraíba, known for its well-preserved colonial architecture and frequent use as a filming location for movies and television.
  • D. Caieiras
    Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
  • E. Espinhal
    Espinhal is a civil parish located in the municipality of Penela in central Portugal, known for its rural landscape and traditional Portuguese village character.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66841b7d88190af3606f762d87b24 completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.