Triple

T5298212
Position Surface form Disambiguated ID Type / Status
Subject Southern Peru E119907 entity
Predicate hasMajorCity P316 FINISHED
Object Cusco E21511 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: Cusco | Statement: [Southern Peru, hasMajorCity, Cusco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cusco
Context triple: [Southern Peru, hasMajorCity, Cusco]
  • A. Cusco chosen
    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.
  • B. 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.
  • C. Juliaca
    Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
  • D. Cajamarca
    Cajamarca is a city in the northern highlands of Peru, historically renowned as the site where Spanish conquistador Francisco Pizarro captured the Inca emperor Atahualpa, marking a pivotal moment in the Spanish conquest of the Inca Empire.
  • E. Abancay
    Abancay is a city in the Andean highlands of Peru, serving as the capital of the Apurímac Region and known for its mild climate and surrounding mountainous landscapes.
  • 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_69bd446f22b88190b6a47fb91c68a3e7 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd85053e3c8190b28648056d6c5710 completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf70c8df3c8190a15baf3ab8985305 completed March 22, 2026, 4:32 a.m.
Created at: March 20, 2026, 1:53 p.m.