Triple

T4926622
Position Surface form Disambiguated ID Type / Status
Subject Andean region E110592 entity
Predicate hasMajorCity P316 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: [Andean region, hasMajorCity, Arequipa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arequipa
Context triple: [Andean region, hasMajorCity, 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. Puno
    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.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70354bd081909291a43439f42ed3 completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81c2cb288190b0a603992c08235c completed March 21, 2026, 11:32 a.m.
Created at: March 20, 2026, 1:30 p.m.