Triple

T4498813
Position Surface form Disambiguated ID Type / Status
Subject Oyón Province E100765 entity
Predicate capital P234 FINISHED
Object Oyón
Oyón is a town in Peru that serves as the administrative and commercial center of the surrounding Oyón Province in the highlands.
 E448072 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: Oyón | Statement: [Oyón Province, capital, Oyón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oyón
Context triple: [Oyón Province, capital, Oyón]
  • A. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • B. Hinojosa
    Hinojosa is a Spanish surname historically associated with figures such as José de la Serna e Hinojosa, the last viceroy of Peru.
  • C. Rivas
    Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
  • D. Aguadas
    Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
  • E. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • 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: Oyón
Triple: [Oyón Province, capital, Oyón]
Generated description
Oyón is a town in Peru that serves as the administrative and commercial center of the surrounding Oyón Province in the highlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oyón
Target entity description: Oyón is a town in Peru that serves as the administrative and commercial center of the surrounding Oyón Province in the highlands.
  • A. Requena
    Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
  • B. Hinojosa
    Hinojosa is a Spanish surname historically associated with figures such as José de la Serna e Hinojosa, the last viceroy of Peru.
  • C. Rivas
    Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
  • D. Aguadas
    Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
  • E. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • 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_69bd43cdf15081909a4fa2585ff63b3e completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56c29868819097633c7cd398e865 completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f89114081908adbd8e78d4c8ec4 completed March 20, 2026, 4:02 p.m.
NEDg Description generation batch_69bd71aecafc8190b0815d0308bbcaa9 completed March 20, 2026, 4:11 p.m.
NED2 Entity disambiguation (via description) batch_69bd75f39d788190b9e394050c55f44d completed March 20, 2026, 4:29 p.m.
Created at: March 20, 2026, 1 p.m.