Triple

T13633922
Position Surface form Disambiguated ID Type / Status
Subject Quispicanchi Province E325796 entity
Predicate locatedIn P40 FINISHED
Object southeastern Peru E118226 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: southeastern Peru | Statement: [Quispicanchi Province, locatedIn, southeastern Peru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: southeastern Peru
Context triple: [Quispicanchi Province, locatedIn, southeastern Peru]
  • A. southeastern Peru chosen
    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. eastern Peru
    Eastern Peru is a remote, sparsely populated region dominated by Amazon rainforest, extensive river systems, and rich biodiversity.
  • 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. Southern Peru
    Southern Peru is a geographic region of Peru known for its Andean highlands, volcanic landscapes, and major cities such as Arequipa and Cusco.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a490508190924ac40f1dd519d6 completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78aef6fd08190b209a94b9ddd024c completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:51 p.m.