Triple

T5108188
Position Surface form Disambiguated ID Type / Status
Subject Manuel Tagüeña E115149 entity
Predicate familyName P18 FINISHED
Object Tagüeña
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
 E493606 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: Tagüeña | Statement: [Manuel Tagüeña, familyName, Tagüeña]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tagüeña
Context triple: [Manuel Tagüeña, familyName, Tagüeña]
  • A. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • B. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • C. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • D. Navarrete
    Navarrete is a Spanish surname most notably borne by Javier Navarrete, an acclaimed film composer known for his work on movies such as "Pan's Labyrinth."
  • E. El Marg
    El Marg is a northeastern district of Cairo known for its dense residential neighborhoods and role as a gateway between the city and its surrounding suburbs.
  • 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: Tagüeña
Triple: [Manuel Tagüeña, familyName, Tagüeña]
Generated description
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tagüeña
Target entity description: Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
  • A. Montalva
    Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
  • B. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • C. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • D. Navarrete
    Navarrete is a Spanish surname most notably borne by Javier Navarrete, an acclaimed film composer known for his work on movies such as "Pan's Labyrinth."
  • E. El Marg
    El Marg is a northeastern district of Cairo known for its dense residential neighborhoods and role as a gateway between the city and its surrounding suburbs.
  • 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75aa6b088190b02cdb66ec4a11f0 completed March 20, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba9ec0fc819085dcd1d27f46f377 completed March 21, 2026, 3:34 p.m.
NEDg Description generation batch_69bebb427ee0819090cc2a7b12310719 completed March 21, 2026, 3:37 p.m.
NED2 Entity disambiguation (via description) batch_69bebbbeaa98819099c8a376a30638d2 completed March 21, 2026, 3:39 p.m.
Created at: March 20, 2026, 1:41 p.m.