Triple

T2717495
Position Surface form Disambiguated ID Type / Status
Subject Peru Time E60001 entity
Predicate usedInCity P4810 FINISHED
Object Juliaca E61910 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: Juliaca | Statement: [Peru Time, usedInCity, Juliaca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juliaca
Context triple: [Peru Time, usedInCity, Juliaca]
  • A. 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.
  • B. 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.
  • C. Puno chosen
    Puno is a city in southeastern Peru on the shores of Lake Titicaca, known as a cultural center of the Andean highlands and a gateway to the lake’s islands.
  • 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. Chimbote
    Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdaad577c8190819d3c641c2406f4 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0311527188190a034820f4ff30d5a completed March 10, 2026, 2:56 p.m.
Created at: March 6, 2026, 9:55 p.m.