Triple

T11955008
Position Surface form Disambiguated ID Type / Status
Subject Ampato E284527 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Arequipa E22142 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: Arequipa | Statement: [Ampato, hasNearbySettlement, Arequipa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arequipa
Context triple: [Ampato, hasNearbySettlement, Arequipa]
  • A. Arequipa chosen
    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.
  • B. Juliaca
    Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
  • C. Chimbote
    Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
  • D. 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.
  • E. Chivay
    Chivay is a small Andean town in southern Peru that serves as the main gateway and service hub for visitors to the Colca Canyon.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90366fda8819083168c93abad27d4 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471c931a88190a9d29262c62b9472 completed May 1, 2026, 9:26 a.m.
Created at: April 8, 2026, 9:45 p.m.