Triple

T4160300
Position Surface form Disambiguated ID Type / Status
Subject Club de la Unión E91515 entity
Predicate region P40 FINISHED
Object Lima Region E14664 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: Lima Region | Statement: [Club de la Unión, region, Lima Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima Region
Context triple: [Club de la Unión, region, Lima Region]
  • A. Lima Region chosen
    Lima Region is an administrative region on the central coast of Peru that surrounds but does not include the country’s capital city, Lima.
  • B. Lima Province
    Lima Province is the coastal Peruvian province that contains the nation’s capital city, Lima, serving as the country’s main political, economic, and cultural hub.
  • C. Cajamarca Region
    Cajamarca Region is an administrative region in northern Peru known for its Andean highlands, rich colonial and pre-Columbian history, and significant mining and agricultural activities.
  • D. Moquegua Region
    Moquegua Region is a sparsely populated region in southern Peru known for its volcanic landscapes, including the active Ubinas volcano, as well as its mining activities and agricultural production.
  • E. Piura Region
    Piura Region is a coastal region in northwestern Peru known for its warm climate, beaches, and agricultural production.
  • 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_69aed9626ebc8190a39de631788bea3e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af029454d08190b7ff32776081fabc completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa0121b48190899cb4be8b87a93b completed March 21, 2026, 1:53 a.m.
Created at: March 9, 2026, 3:44 p.m.