Triple

T733629
Position Surface form Disambiguated ID Type / Status
Subject Valparaíso E14881 entity
Predicate sisterCity P1072 FINISHED
Object La Plata E86152 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: La Plata | Statement: [Valparaíso, sisterCity, La Plata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Plata
Context triple: [Valparaíso, sisterCity, La Plata]
  • A. La Plata chosen
    La Plata is the planned capital city of Argentina’s Buenos Aires Province, known for its distinctive diagonal street grid and cultural and educational institutions.
  • B. Buenos Aires
    Buenos Aires is the capital and largest city of Argentina, known for its rich European-influenced culture, tango music and dance, and vibrant urban life.
  • C. Colonia Buenos Aires
    Colonia Buenos Aires is a neighborhood located within the Cuauhtémoc borough in central Mexico City.
  • D. La Boca
    La Boca is a colorful, working-class neighborhood in Buenos Aires famous for its vividly painted houses, tango culture, and the Boca Juniors football stadium.
  • E. Santa Fe, Argentina
    Santa Fe, Argentina is a major river port city and the capital of Santa Fe Province, located in northeastern Argentina along the Paraná and Salado rivers.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5d6cc58819082018cdfa14b37df completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6666ebf2c8190b0b0f1b9aa8ac12d completed March 3, 2026, 4:41 a.m.
Created at: March 1, 2026, 7:37 p.m.