Triple

T8376542
Position Surface form Disambiguated ID Type / Status
Subject Buenos Aires Underground Line A E197590 entity
Predicate servesNeighborhood P82 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: [Buenos Aires Underground Line A, servesNeighborhood, Almagro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Almagro
Context triple: [Buenos Aires Underground Line A, servesNeighborhood, Almagro]
  • A. Almagro
    Almagro is a Spanish surname borne by various notable figures, including politicians, athletes, and artists from Spanish-speaking countries.
  • B. 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.
  • 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. Ancud
    Ancud is a coastal city on northern Chiloé Island in southern Chile, known historically as a Spanish stronghold and for its maritime heritage and nearby natural landscapes.
  • 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_69ca82f64c188190af4e1608036b865d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80c094908190afe9cc54ce4f4d58 completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d14baf88190bc260efda7d0fc0d completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:01 p.m.