Triple

T14198230
Position Surface form Disambiguated ID Type / Status
Subject Santa Cruz das Flores E351895 entity
Predicate municipality P852 FINISHED
Object Santa Cruz das Flores E351895 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: Santa Cruz das Flores | Statement: [Santa Cruz das Flores, municipality, Santa Cruz das Flores]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Cruz das Flores
Context triple: [Santa Cruz das Flores, municipality, Santa Cruz das Flores]
  • A. Santa Cruz das Flores chosen
    Santa Cruz das Flores is the main town and administrative center of Flores Island in Portugal’s Azores archipelago.
  • B. Santa Cruz do Sul
    Santa Cruz do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage, architecture, and traditions.
  • C. São Sebastião
    São Sebastião is a coastal municipality in the state of São Paulo, Brazil, known for its beaches, tourism, and role as a port city.
  • D. São Sebastião
    São Sebastião is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
  • E. São Fidélis
    São Fidélis is a municipality in the state of Rio de Janeiro, Brazil, known for its historic architecture and location along the Paraíba do Sul River.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61e30f208190b61c1c7bd3501156 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd194d14008190a74021ff5a3e51d1 completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:04 a.m.