Triple

T10637970
Position Surface form Disambiguated ID Type / Status
Subject Palermo Hollywood E250642 entity
Predicate partOf P40 FINISHED
Object Comuna 14 E250654 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: Comuna 14 | Statement: [Palermo Hollywood, partOf, Comuna 14]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Comuna 14
Context triple: [Palermo Hollywood, partOf, Comuna 14]
  • A. Comuna 4
    Comuna 4 is an administrative commune of Buenos Aires that includes neighborhoods such as La Boca in the city’s southern area.
  • B. Comuna 3
    Comuna 3 is an administrative division of Buenos Aires, Argentina, that encompasses central neighborhoods including Balvanera.
  • C. Comuna 14 of Buenos Aires chosen
    Comuna 14 of Buenos Aires is an administrative district of the city best known for encompassing the Palermo neighborhood, a major cultural, commercial, and residential hub.
  • D. Comuna 13
    Comuna 13 is an administrative division of the city of Buenos Aires that encompasses several northern neighborhoods, including Núñez.
  • E. María Elena Commune
    María Elena Commune is an administrative division in Chile’s Antofagasta Region, historically known for its nitrate mining industry and desert landscape.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfae51148190840a4e52b29ad06e completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bc57a8081908abd73f4273d0666 completed April 10, 2026, 9:29 p.m.
Created at: April 8, 2026, 9:04 p.m.