Triple

T17376648
Position Surface form Disambiguated ID Type / Status
Subject Sierra (Peru) E422453 entity
Predicate borders P224 FINISHED
Object Costa (Peru)
Costa (Peru) is the long, arid-to-subtropical coastal region of Peru along the Pacific Ocean, encompassing many of the country’s major cities and economic centers.
 E1266335 NE FINISHED

How this triple was built (4 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: Costa (Peru) | Statement: [Sierra (Peru), borders, Costa (Peru)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Costa (Peru)
Context triple: [Sierra (Peru), borders, Costa (Peru)]
  • A. El Paraíso (Peru)
    El Paraíso (Peru) is an ancient preceramic archaeological complex near Lima, notable as one of the earliest large-scale monumental centers in the central Andes.
  • B. Costa Sur
    Costa Sur is a coastal region in the Mexican state of Jalisco known for its Pacific beaches, fishing villages, and tourism.
  • C. Costa
    Costa is a Chilean wine-producing subregion within the Cachapoal Valley, known for its coastal influence that shapes the style and character of its wines.
  • D. Costa
    Costa is the low-lying, tropical coastal region of Ecuador known for its beaches, port cities, and agricultural production.
  • E. Costa
    Costa is a common Portuguese surname borne by numerous notable figures in politics, sports, and the arts.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Costa (Peru)
Triple: [Sierra (Peru), borders, Costa (Peru)]
Generated description
Costa (Peru) is the long, arid-to-subtropical coastal region of Peru along the Pacific Ocean, encompassing many of the country’s major cities and economic centers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Costa (Peru)
Target entity description: Costa (Peru) is the long, arid-to-subtropical coastal region of Peru along the Pacific Ocean, encompassing many of the country’s major cities and economic centers.
  • A. El Paraíso (Peru)
    El Paraíso (Peru) is an ancient preceramic archaeological complex near Lima, notable as one of the earliest large-scale monumental centers in the central Andes.
  • B. Costa Sur
    Costa Sur is a coastal region in the Mexican state of Jalisco known for its Pacific beaches, fishing villages, and tourism.
  • C. Costa
    Costa is a Chilean wine-producing subregion within the Cachapoal Valley, known for its coastal influence that shapes the style and character of its wines.
  • D. Costa
    Costa is a common Portuguese surname borne by numerous notable figures in politics, sports, and the arts.
  • E. Costa
    Costa is the low-lying, tropical coastal region of Ecuador known for its beaches, port cities, and agricultural production.
  • F. None of above. chosen

Provenance (5 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a6ddbd081908908b953597977d2 completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019ff344a881908f0870ac7ce8e120 completed May 11, 2026, 9:22 a.m.
NEDg Description generation batch_6a01a089ac0081908a746c0c25cc12be completed May 11, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_6a01a1c415dc8190ba8f7e2a8053917f completed May 11, 2026, 9:30 a.m.
Created at: April 10, 2026, 5:45 a.m.