Triple

T20027114
Position Surface form Disambiguated ID Type / Status
Subject Carazo E495012 entity
Predicate hasCity P316 FINISHED
Object Santa Teresa 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: Santa Teresa | Statement: [Carazo, hasCity, Santa Teresa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Teresa
Context triple: [Carazo, hasCity, Santa Teresa]
  • A. Santa Teresa
    Santa Teresa is a historic, bohemian hilltop neighborhood in Rio de Janeiro known for its winding streets, colonial mansions, and vibrant arts scene.
  • B. Santa Teresa chosen
    Santa Teresa is a small, historically Italian-immigrant town in southeastern Brazil known for its cool mountain climate, colonial architecture, and ecotourism.
  • C. Santa Tereza
    Santa Tereza is a small wine-producing town in Brazil’s Serra Gaúcha region, known for its Italian heritage and scenic mountain landscapes.
  • D. Santa Teresa Cora
    Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
  • E. Santa Teresa del Tuy
    Santa Teresa del Tuy is a principal urban center in the Valles del Tuy region of Miranda state, Venezuela, known for its role as a local commercial and transportation hub.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6628e1eec81908e4c9b2b0b68f0e4 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.