Triple

T8106248
Position Surface form Disambiguated ID Type / Status
Subject Boca E189233 entity
Predicate neighborhood P988 FINISHED
Object La Boca E37033 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: La Boca | Statement: [Boca, neighborhood, La Boca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Boca
Context triple: [Boca, neighborhood, La Boca]
  • A. La Boca chosen
    La Boca is a colorful, working-class neighborhood in Buenos Aires famous for its vividly painted houses, tango culture, and the Boca Juniors football stadium.
  • B. Puerto Madero
    Puerto Madero is a revitalized waterfront neighborhood in Buenos Aires known for its modern high-rises, upscale dining, and contemporary urban development along the old port docks.
  • C. 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.
  • D. Vicente López
    Vicente López is a suburban partido (district) in the northern Greater Buenos Aires area of Argentina, known for its residential neighborhoods and riverside parks along the Río de la Plata.
  • E. San Nicolás
    San Nicolás is a central Buenos Aires neighborhood known as a major commercial and cultural hub that includes landmarks like the Obelisco and the city’s main theater district.
  • 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_69ca82b9d5848190a24672775d5c5011 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42f735c8819090d0d822644c0a51 completed March 31, 2026, 3:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd677b00548190929a2a38b4d1476f completed April 1, 2026, 6:44 p.m.
Created at: March 30, 2026, 5:31 p.m.