Triple

T9822494
Position Surface form Disambiguated ID Type / Status
Subject Barracas E238568 entity
Predicate borderedBy P224 FINISHED
Object Avellaneda E329768 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: Avellaneda | Statement: [Barracas, borderedBy, Avellaneda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avellaneda
Context triple: [Barracas, borderedBy, Avellaneda]
  • A. Avellaneda chosen
    Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
  • B. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • C. Almagro
    Almagro is a traditional middle-class neighborhood in central Buenos Aires, Argentina, known for its historic tango culture, cafes, and densely populated residential streets.
  • D. Almagro
    Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
  • E. 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.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb315ddf48190bd90f7835f409bb6 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc7ce1908190a5131ef238541f0d completed April 5, 2026, 2:44 a.m.
Created at: March 30, 2026, 8:31 p.m.