Triple

T14012349
Position Surface form Disambiguated ID Type / Status
Subject Christina of Norway E337113 entity
Predicate residence P75 FINISHED
Object Covarrubias
Covarrubias is a historic village in the province of Burgos, Spain, known for its medieval architecture and ties to Castilian nobility.
E1073062 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: Covarrubias | Statement: [Christina of Norway, residence, Covarrubias]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Covarrubias
Context triple: [Christina of Norway, residence, Covarrubias]
  • A. Covarrubias
    Covarrubias is a Spanish surname most notably associated with Renaissance architect and sculptor Alonso de Covarrubias, whose work significantly shaped the Plateresque style.
  • B. Ceballos
    Ceballos is a Spanish surname borne by various notable figures in politics, sports, and the arts.
  • C. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • D. Carrillo
    Carrillo is a Spanish-origin surname borne by numerous notable individuals across the Spanish-speaking world and beyond.
  • E. Balderas
    Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
  • 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: Covarrubias
Triple: [Christina of Norway, residence, Covarrubias]
Generated description
Covarrubias is a historic village in the province of Burgos, Spain, known for its medieval architecture and ties to Castilian nobility.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Covarrubias
Target entity description: Covarrubias is a historic village in the province of Burgos, Spain, known for its medieval architecture and ties to Castilian nobility.
  • A. Covarrubias
    Covarrubias is a Spanish surname most notably associated with Renaissance architect and sculptor Alonso de Covarrubias, whose work significantly shaped the Plateresque style.
  • B. Ceballos
    Ceballos is a Spanish surname borne by various notable figures in politics, sports, and the arts.
  • C. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • D. Carrillo
    Carrillo is a Spanish-origin surname borne by numerous notable individuals across the Spanish-speaking world and beyond.
  • E. Balderas
    Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbacaa16e88190995fd86951fb54e6 completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbada0a2408190b77d163aee17400e completed May 6, 2026, 9:07 p.m.
NED2 Entity disambiguation (via description) batch_69fbaeeeb594819087b57da166495a72 completed May 6, 2026, 9:13 p.m.
Created at: April 9, 2026, 10:19 p.m.