Triple

T2437215
Position Surface form Disambiguated ID Type / Status
Subject Avianca E52987 entity
Predicate focusCity P164 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: [Avianca, focusCity, Guatemala City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guatemala City
Context triple: [Avianca, focusCity, 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. San Pedro Sula
    San Pedro Sula is a large industrial and commercial city in northern Honduras, historically known as the country’s economic hub.
  • C. San Salvador
    San Salvador is the largest city of El Salvador and its political, cultural, and economic center.
  • D. Antigua Guatemala
    Antigua Guatemala is a historic colonial city in southern Guatemala renowned for its well-preserved Spanish Baroque architecture and cobblestone streets, and is recognized as a UNESCO World Heritage Site.
  • E. Tegucigalpa
    Tegucigalpa is the capital and largest city of Honduras, serving as 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f342e88190a430b02842ded418 completed March 7, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0ad31b8819084813b65b46bc9fc completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:43 p.m.