Triple

T17829161
Position Surface form Disambiguated ID Type / Status
Subject Rosario Department E445202 entity
Predicate borderedBy P224 FINISHED
Object San Lorenzo Department NE NERFINISHED

How this triple was built (3 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: San Lorenzo Department | Statement: [Rosario Department, borderedBy, San Lorenzo Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Lorenzo Department
Context triple: [Rosario Department, borderedBy, San Lorenzo Department]
  • A. San Miguel Department
    San Miguel Department is an administrative division in eastern El Salvador that includes the city of San Miguel as its capital and economic center.
  • B. San Rafael Department
    San Rafael Department is an administrative subdivision in Mendoza Province, Argentina, centered on the city of San Rafael and known for its wine production and tourism.
  • C. San Vicente Department
    San Vicente Department is an administrative region in central El Salvador known for its agricultural economy and as the site of significant events during the country’s civil war.
  • D. Maldonado Department
    Maldonado Department is an administrative region in southeastern Uruguay known for its Atlantic coastline, tourism industry, and popular resort city Punta del Este.
  • E. Rosario Department
    Rosario Department is an administrative division in the Santa Fe Province of Argentina, centered around the major city of Rosario and known for its economic and cultural significance.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: San Lorenzo Department
Target entity description: San Lorenzo Department is an administrative division in the province of Santa Fe, Argentina, known for its industrial activity and strategic location along the Paraná River.
  • A. San Miguel Department
    San Miguel Department is an administrative division in eastern El Salvador that includes the city of San Miguel as its capital and economic center.
  • B. San Rafael Department
    San Rafael Department is an administrative subdivision in Mendoza Province, Argentina, centered on the city of San Rafael and known for its wine production and tourism.
  • C. San Vicente Department
    San Vicente Department is an administrative region in central El Salvador known for its agricultural economy and as the site of significant events during the country’s civil war.
  • D. Maldonado Department
    Maldonado Department is an administrative region in southeastern Uruguay known for its Atlantic coastline, tourism industry, and popular resort city Punta del Este.
  • E. Rosario Department
    Rosario Department is an administrative division in the Santa Fe Province of Argentina, centered around the major city of Rosario and known for its economic and cultural significance.
  • F. None of above. chosen

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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4891696cc819092ee6db7c4a6fae1 completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.