Triple

T9196947
Position Surface form Disambiguated ID Type / Status
Subject Balvanera E220738 entity
Predicate borderedBy P224 FINISHED
Object Almagro E717929 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: Almagro | Statement: [Balvanera, borderedBy, Almagro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almagro
Context triple: [Balvanera, borderedBy, Almagro]
  • A. Almagro chosen
    Almagro is a traditional middle-class neighborhood in central Buenos Aires, Argentina, known for its historic tango culture, cafes, and densely populated residential streets.
  • B. Almagro
    Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
  • C. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • D. Moncalvo
    Moncalvo is a small historic town in Italy’s Piedmont region, known as one of the country’s smallest cities and for its wine and truffle production.
  • E. Balcarce
    Balcarce is a city in Buenos Aires Province, Argentina, known for its agricultural economy, motorsport heritage, and as the birthplace of racing legend Juan Manuel Fangio.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd87d6460819097234b5dd3f749b4 completed April 1, 2026, 8:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09b8b37488190b72f2b4c55fd9a8c completed April 4, 2026, 5:03 a.m.
Created at: March 30, 2026, 7:25 p.m.