Triple

T5298495
Position Surface form Disambiguated ID Type / Status
Subject Colca Canyon E119914 entity
Predicate hasSettlementNearby P7611 FINISHED
Object Chivay E518200 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: Chivay | Statement: [Colca Canyon, hasSettlementNearby, Chivay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chivay
Context triple: [Colca Canyon, hasSettlementNearby, Chivay]
  • A. Chivay chosen
    Chivay is a small Andean town in southern Peru that serves as the main gateway and service hub for visitors to the Colca Canyon.
  • B. Colina
    Colina is a commune and city in central Chile known for its growing residential areas and proximity to Santiago in the Santiago Metropolitan Region.
  • C. Chimbote
    Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
  • D. Huancayo
    Huancayo is a major city in the central highlands of Peru, known as a commercial and cultural hub of the Mantaro Valley.
  • 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_69bd8506a90c8190bf311f280a061d1a completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4114c120819098c2fcc7d1357441 completed March 22, 2026, 1:08 a.m.
Created at: March 20, 2026, 1:53 p.m.