Triple

T2405541
Position Surface form Disambiguated ID Type / Status
Subject Loreto Region E50268 entity
Predicate largestCity P235 FINISHED
Object Iquitos E22698 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: Iquitos | Statement: [Loreto Region, largestCity, Iquitos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Iquitos
Context triple: [Loreto Region, largestCity, Iquitos]
  • A. Iquitos chosen
    Iquitos is a major Peruvian city in the Amazon rainforest, known as one of the world’s largest cities accessible only by river and air.
  • B. Lima
    Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
  • C. Arequipa
    Arequipa is Peru’s second-largest city, known for its colonial architecture built from white volcanic stone and its dramatic setting beneath the Misti volcano.
  • D. Sucre
    Sucre is the constitutional capital of Bolivia, known for its well-preserved colonial architecture and historical significance in the country’s independence.
  • E. Cusco
    Cusco is a historic city in southeastern Peru that served as the capital of the Inca Empire and is now a major gateway to Machu Picchu.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc8fb78408190b99fa8b4dfaaa75d completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf403f74819082dc50e31f29b171 completed March 9, 2026, 12:38 p.m.
Created at: March 4, 2026, 7:58 p.m.