Triple

T11364785
Position Surface form Disambiguated ID Type / Status
Subject Álvaro de Luna E269174 entity
Predicate placeOfBirth P1 FINISHED
Object Cañete
Cañete is a historic town in the province of Cuenca, Spain, known for its medieval architecture and hilltop castle.
 E921567 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: Cañete | Statement: [Álvaro de Luna, placeOfBirth, Cañete]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cañete
Context triple: [Álvaro de Luna, placeOfBirth, Cañete]
  • A. Cañete
    Cañete is a coastal province and agricultural hub in central Peru, known for its fertile valleys, Afro-Peruvian cultural heritage, and production of crops like grapes and cotton.
  • B. Peñafiel
    Peñafiel is a historic town in Spain renowned for its medieval castle and wine-making tradition in the Ribera del Duero region.
  • C. Puntallana
    Puntallana is a small coastal municipality and rural village on the northeastern side of the island of La Palma in Spain’s Canary Islands.
  • D. Vizcaína
    Vizcaína was one of the ships in Christopher Columbus’s fourth voyage to the Americas in the early 16th century.
  • E. Ubaque
    Ubaque is a municipality in central Colombia known for its rural Andean landscapes and traditional agricultural communities.
  • 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: Cañete
Triple: [Álvaro de Luna, placeOfBirth, Cañete]
Generated description
Cañete is a historic town in the province of Cuenca, Spain, known for its medieval architecture and hilltop castle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cañete
Target entity description: Cañete is a historic town in the province of Cuenca, Spain, known for its medieval architecture and hilltop castle.
  • A. Cañete
    Cañete is a coastal province and agricultural hub in central Peru, known for its fertile valleys, Afro-Peruvian cultural heritage, and production of crops like grapes and cotton.
  • B. Peñafiel
    Peñafiel is a historic town in Spain renowned for its medieval castle and wine-making tradition in the Ribera del Duero region.
  • C. Puntallana
    Puntallana is a small coastal municipality and rural village on the northeastern side of the island of La Palma in Spain’s Canary Islands.
  • D. Vizcaína
    Vizcaína was one of the ships in Christopher Columbus’s fourth voyage to the Americas in the early 16th century.
  • E. Ubaque
    Ubaque is a municipality in central Colombia known for its rural Andean landscapes and traditional agricultural communities.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea4589908190948a8225768e1eec completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e55667d4908190b6290135eba41e54 completed April 19, 2026, 10:25 p.m.
NEDg Description generation batch_69e562c6e7c8819098d22a6e0daa4a51 completed April 19, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69e56a472f0c819086c1cccaa5ca0ae7 completed April 19, 2026, 11:50 p.m.
Created at: April 8, 2026, 9:33 p.m.