Triple

T10804636
Position Surface form Disambiguated ID Type / Status
Subject Lluís Domènech i Montaner E254929 entity
Predicate workLocation P7 FINISHED
Object Comillas
Comillas is a coastal town in Cantabria, northern Spain, noted for its modernist architecture and historic buildings.
 E886684 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: Comillas | Statement: [Lluís Domènech i Montaner, workLocation, Comillas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Comillas
Context triple: [Lluís Domènech i Montaner, workLocation, Comillas]
  • A. Tagüeña
    Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
  • B. Barra
    Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
  • C. Barra
    Barra is the surname of Mary Barra, the prominent American business executive and CEO of General Motors.
  • D. Barra
    Barra is an Arabic female given name historically borne by early Islamic-era women, including relatives of the Prophet Muhammad.
  • E. Avellaneda
    Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
  • 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: Comillas
Triple: [Lluís Domènech i Montaner, workLocation, Comillas]
Generated description
Comillas is a coastal town in Cantabria, northern Spain, noted for its modernist architecture and historic buildings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Comillas
Target entity description: Comillas is a coastal town in Cantabria, northern Spain, noted for its modernist architecture and historic buildings.
  • A. Tagüeña
    Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
  • B. Barra
    Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
  • C. Barra
    Barra is the surname of Mary Barra, the prominent American business executive and CEO of General Motors.
  • D. Barra
    Barra is an Arabic female given name historically borne by early Islamic-era women, including relatives of the Prophet Muhammad.
  • E. Avellaneda
    Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73370e7388190885b104fc883456e completed April 9, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69de567a7ea0819088a2fa10f8367d89 completed April 14, 2026, 3 p.m.
NEDg Description generation batch_69de5eaf3cc08190935cb6ddf2020166 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de63a902f4819089845bc6d7469c6b completed April 14, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:18 p.m.