Triple

T13579574
Position Surface form Disambiguated ID Type / Status
Subject Comarca of Tarragonès E324376 entity
Predicate containsMunicipality P852 FINISHED
Object Vila-seca E1034014 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: Vila-seca | Statement: [Comarca of Tarragonès, containsMunicipality, Vila-seca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vila-seca
Context triple: [Comarca of Tarragonès, containsMunicipality, 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. Canudos do Vale
    Canudos do Vale is a small municipality located in the Vale do Taquari region of the state of Rio Grande do Sul in southern Brazil.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb03052088190a2b68c106059828e completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bbdb2d0819089f094e57dde28cf completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:48 p.m.