Triple

T4990438
Position Surface form Disambiguated ID Type / Status
Subject Santiago E112115 entity
Predicate containsMunicipality P852 FINISHED
Object Santa Catarina E210893 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 Catarina | Statement: [Santiago, containsMunicipality, Santa Catarina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Catarina
Context triple: [Santiago, containsMunicipality, Santa Catarina]
  • A. Santa Catarina chosen
    Santa Catarina is an industrial and residential city in the Monterrey metropolitan area of the Mexican state of Nuevo León.
  • B. Santa Catarina
    Santa Catarina is a southern Brazilian state known for its strong German cultural heritage, picturesque coastal and mountainous landscapes, and significant industrial and agricultural economy.
  • C. Santa Catarina
    Santa Catarina is a neighborhood in Mexico City known for its residential character and proximity to the Miguel Ángel de Quevedo metro station.
  • D. Rio Grande do Sul
    Rio Grande do Sul is Brazil’s southernmost state, known for its gaucho culture, strong agricultural economy, and shared borders with Uruguay and Argentina.
  • E. Paraná state
    Paraná state is a southern Brazilian state known for its diverse landscapes, major agricultural production, and popular natural attractions including part of the Iguaçu National Park.
  • 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_69bd441be7bc8190b530362d427b97d2 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd727fe55881909d42e41b832b9ece completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a282dd08190a29b92e8e825a3bb completed March 21, 2026, 12:08 p.m.
Created at: March 20, 2026, 1:34 p.m.