Triple

T979558
Position Surface form Disambiguated ID Type / Status
Subject Manuel Azaña E21135 entity
Predicate familyName P18 FINISHED
Object Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
 E124317 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: Azaña | Statement: [Manuel Azaña, familyName, Azaña]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Azaña
Context triple: [Manuel Azaña, familyName, Azaña]
  • A. Spínola
    Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
  • B. Cervera
    Cervera is a Spanish surname historically associated with notable figures such as Admiral Pascual Cervera y Topete.
  • C. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • D. Anzures
    Anzures is an upscale residential and commercial neighborhood in Mexico City known for its central location, embassies, and proximity to major business and cultural districts.
  • E. Davila
    Davila is an Italian surname most notably associated with the 17th-century historian Enrico Caterino Davila.
  • 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: Azaña
Triple: [Manuel Azaña, familyName, Azaña]
Generated description
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Azaña
Target entity description: Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
  • A. Spínola
    Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
  • B. Cervera
    Cervera is a Spanish surname historically associated with notable figures such as Admiral Pascual Cervera y Topete.
  • C. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • D. Anzures
    Anzures is an upscale residential and commercial neighborhood in Mexico City known for its central location, embassies, and proximity to major business and cultural districts.
  • E. Davila
    Davila is an Italian surname most notably associated with the 17th-century historian Enrico Caterino Davila.
  • 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_69a493c2b62c8190b616351789ec47f8 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b479e8f081908183448c36244e1f completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4289acc88190886ac8971297b1f8 completed March 7, 2026, 3:21 p.m.
NEDg Description generation batch_69ac4365965881909ff2cdf8eda07f91 completed March 7, 2026, 3:25 p.m.
NED2 Entity disambiguation (via description) batch_69ac43d1cd1c8190852f8811703ebd5f completed March 7, 2026, 3:27 p.m.
Created at: March 1, 2026, 7:40 p.m.