Triple

T13615125
Position Surface form Disambiguated ID Type / Status
Subject Buenos Aires theatre E325291 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Abasto E784058 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: Abasto | Statement: [Buenos Aires theatre, hasNeighbourhood, Abasto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abasto
Context triple: [Buenos Aires theatre, hasNeighbourhood, Abasto]
  • A. Abasto chosen
    Abasto is a Buenos Aires neighborhood best known for its historic central market building and strong cultural association with tango and Carlos Gardel.
  • B. Berazategui
    Berazategui is a city in the Buenos Aires Province of Argentina, known as a suburban part of Greater Buenos Aires with both residential areas and industrial activity.
  • C. 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.
  • D. Morón
    Morón is a city in the western part of the Greater Buenos Aires metropolitan area in Argentina, known as an important residential and commercial hub.
  • E. San Nicolás
    San Nicolás is a commonly used shortened name for San Nicolás de los Garza, a major suburban city in the Monterrey metropolitan area of Nuevo León, Mexico.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0ad0a7c81909c7972187202db96 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f9cbc388190972e949324144d2f completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.