Triple

T20366732
Position Surface form Disambiguated ID Type / Status
Subject Matarani E496929 entity
Predicate serves P98 FINISHED
Object southern Peru NE NERFINISHED

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: southern Peru | Statement: [Matarani, serves, southern Peru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: southern Peru
Context triple: [Matarani, serves, southern Peru]
  • A. southeastern Peru
    Southeastern Peru is a region of the country that includes the historic Andean area around Cusco and extends toward the Amazon Basin.
  • B. northern Peru
    Northern Peru is a geographic region of Peru known for its Andean highlands, rich pre-Columbian archaeological sites, and diverse coastal and jungle landscapes.
  • C. Southern Peru chosen
    Southern Peru is a geographic region of Peru known for its Andean highlands, volcanic landscapes, and major cities such as Arequipa and Cusco.
  • D. western Peru
    Western Peru is the coastal and Andean region of Peru that includes major urban centers such as Lima and is characterized by arid Pacific shores and the western slopes of the Andes.
  • E. eastern Peru
    Eastern Peru is a remote, sparsely populated region dominated by Amazon rainforest, extensive river systems, and rich biodiversity.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a4f9b081908a5a021919c21ccb completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6787291d88190a526fe2461d2a7c6 completed April 20, 2026, 7:03 p.m.
Created at: April 16, 2026, 11:26 a.m.