Triple

T3340021
Position Surface form Disambiguated ID Type / Status
Subject Santiago de Liniers E70234 entity
Predicate residence P75 FINISHED
Object Buenos Aires E5323 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: Buenos Aires | Statement: [Santiago de Liniers, residence, Buenos Aires]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buenos Aires
Context triple: [Santiago de Liniers, residence, Buenos Aires]
  • A. Buenos Aires chosen
    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.
  • B. Mar del Plata
    Mar del Plata is a major Argentine Atlantic coastal city renowned as a popular beach resort and tourist destination.
  • C. Colonia Buenos Aires
    Colonia Buenos Aires is a neighborhood located within the Cuauhtémoc borough in central Mexico City.
  • D. Montevideo
    Montevideo is the capital and largest city of Uruguay, serving as the country’s main political, economic, and cultural center.
  • E. La Plata
    La Plata, historically known as the city of Sucre in present-day Bolivia, is a colonial-era Andean city that served as an important administrative and judicial center of the Spanish Empire in South America.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bf1f648190993ac8e9dda60983 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b325191a38819095cdccca8f013774 completed March 12, 2026, 8:42 p.m.
Created at: March 8, 2026, 3:12 p.m.