Triple

T16025157
Position Surface form Disambiguated ID Type / Status
Subject Salón de Banderas E388698 entity
Predicate locatedInCity P40 FINISHED
Object Guatemala City E16269 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: Guatemala City | Statement: [Salón de Banderas, locatedInCity, Guatemala City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guatemala City
Context triple: [Salón de Banderas, locatedInCity, Guatemala City]
  • A. Guatemala City chosen
    Guatemala City is the capital and largest city of Guatemala, serving as the country’s political, economic, and cultural center.
  • B. Siguatepeque
    Siguatepeque is a Honduran city known as an important commercial and agricultural center in the country’s central highlands.
  • C. Santiago Atitlán
    Santiago Atitlán is a traditional Tz'utujil Maya town in Guatemala known for its vibrant indigenous culture, crafts, and scenic location on the shores of Lake Atitlán.
  • D. San Pedro Sula
    San Pedro Sula is a large industrial and commercial city in northern Honduras, historically known as the country’s economic hub.
  • E. San Salvador
    San Salvador is the largest city of El Salvador and its political, cultural, and economic center.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1832790548190a74045d554e13328 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf31c8d8819096c562ba1453f3c0 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:55 a.m.