Triple

T8796709
Position Surface form Disambiguated ID Type / Status
Subject Convento de Santa Teresa E209306 entity
Predicate neighborhood P988 FINISHED
Object Santa Teresa E39169 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 Teresa | Statement: [Convento de Santa Teresa, neighborhood, Santa Teresa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Teresa
Context triple: [Convento de Santa Teresa, neighborhood, Santa Teresa]
  • A. Santa Teresa chosen
    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 Cora
    Santa Teresa Cora is a regional dialect of the Cora language spoken by the indigenous Cora people of western Mexico.
  • C. Santa Rosa de Lima
    Santa Rosa de Lima is a 17th-century Peruvian mystic and member of the Dominican Order venerated as the first canonized saint of the Americas and the patron saint of Peru and Latin America.
  • D. Santa Isabel
    Santa Isabel is a supermarket chain in Latin America operated under the retail group Cencosud.
  • E. Santa Isabel
    Santa Isabel was the colonial capital city of Spanish Equatorial Guinea, serving as the administrative and political center during Spanish rule.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa370d08190885ef65e3a3e56d3 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1bbf6b881909bc154caa2fcadbe completed April 3, 2026, 1:33 p.m.
Created at: March 30, 2026, 6:44 p.m.