Triple

T6289254
Position Surface form Disambiguated ID Type / Status
Subject Iguazu River E140973 entity
Predicate nearbyCity P350 FINISHED
Object Ciudad del Este E151507 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: Ciudad del Este | Statement: [Iguazu River, nearbyCity, Ciudad del Este]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ciudad del Este
Context triple: [Iguazu River, nearbyCity, Ciudad del Este]
  • A. Ciudad del Este chosen
    Ciudad del Este is a major commercial city in eastern Paraguay, known as a busy border trading hub near the tri-border area with Brazil and Argentina.
  • B. Paysandú
    Paysandú is a major city in western Uruguay known as an important industrial and port center near the Argentine border.
  • C. Ciudad de Corrientes
    Ciudad de Corrientes is the capital city of the Corrientes Province in northeastern Argentina, known for its colonial architecture and location along the Paraná River.
  • D. Luque, Paraguay
    Luque is a city in the Central Department of Paraguay, part of the Greater Asunción metropolitan area and an important administrative and commercial center.
  • E. Tacuarembó
    Tacuarembó is a city in northern Uruguay that serves as the capital of Tacuarembó Department and a regional center for culture, education, and services.
  • 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_69c008cd17c8819082b82d3fbeb68047 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0641a6ecc8190a63be0e3f0344a3f completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c673f891d08190ad10070bc3a71d76 completed March 27, 2026, 12:11 p.m.
Created at: March 22, 2026, 4:26 p.m.