Triple

T12920494
Position Surface form Disambiguated ID Type / Status
Subject Ricardo Ehrlich E309104 entity
Predicate residence P75 FINISHED
Object Montevideo E47651 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: Montevideo | Statement: [Ricardo Ehrlich, residence, Montevideo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montevideo
Context triple: [Ricardo Ehrlich, residence, Montevideo]
  • A. Montevideo chosen
    Montevideo is the capital and largest city of Uruguay, serving as the country’s main political, economic, and cultural center.
  • 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. San José, Uruguay
    San José, Uruguay is a small city in southern Uruguay that serves as the capital of the San José Department and is known for its agricultural surroundings and colonial-era heritage.
  • D. Ciudad del Este
    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.
  • E. Bahía Blanca
    Bahía Blanca is a major port city in southern Buenos Aires Province, Argentina, known for its industrial activity and strategic location on the Atlantic coast.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971e7f6e881908c7bb12283898c80 completed April 10, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbbccbd08190869d8de09797bc6a completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 5:41 p.m.