Triple

T11433340
Position Surface form Disambiguated ID Type / Status
Subject Almagro E270941 entity
Predicate hasVariant P455 FINISHED
Object de Almagro
De Almagro is a variant form of the Spanish surname Almagro, historically associated with figures such as the conquistador Diego de Almagro.
E925985 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: de Almagro | Statement: [Almagro, hasVariant, de Almagro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: de Almagro
Context triple: [Almagro, hasVariant, de Almagro]
  • A. de Luna
    De Luna is the noble Aragonese family name of Pope Benedict XIII, reflecting his origins in the medieval Spanish aristocracy.
  • B. Simancas
    Simancas is a historic town in Spain renowned for its royal archive, which houses some of the country’s most important state documents.
  • C. Portolá
    Portolá is a Spanish surname most notably associated with Gaspar de Portolá, the 18th-century explorer and first Spanish governor of Alta California.
  • D. Ortiz de Gaete
    Ortiz de Gaete is a Spanish surname historically associated with the family of Marina Ortiz de Gaete, wife of conquistador Pedro de Valdivia.
  • E. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • 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: de Almagro
Triple: [Almagro, hasVariant, de Almagro]
Generated description
De Almagro is a variant form of the Spanish surname Almagro, historically associated with figures such as the conquistador Diego de Almagro.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: de Almagro
Target entity description: De Almagro is a variant form of the Spanish surname Almagro, historically associated with figures such as the conquistador Diego de Almagro.
  • A. de Luna
    De Luna is the noble Aragonese family name of Pope Benedict XIII, reflecting his origins in the medieval Spanish aristocracy.
  • B. Simancas
    Simancas is a historic town in Spain renowned for its royal archive, which houses some of the country’s most important state documents.
  • C. Portolá
    Portolá is a Spanish surname most notably associated with Gaspar de Portolá, the 18th-century explorer and first Spanish governor of Alta California.
  • D. Ortiz de Gaete
    Ortiz de Gaete is a Spanish surname historically associated with the family of Marina Ortiz de Gaete, wife of conquistador Pedro de Valdivia.
  • E. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d806c485f481909dd3d9b0993f3faf completed April 9, 2026, 8:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d379f8d48190860a1ef98505c42e completed April 20, 2026, 7:19 a.m.
NEDg Description generation batch_69e5d659fd7c819090b168168e355cb8 completed April 20, 2026, 7:31 a.m.
NED2 Entity disambiguation (via description) batch_69e5d7f238cc8190a1c2dd26bdc5ff77 completed April 20, 2026, 7:38 a.m.
Created at: April 8, 2026, 9:35 p.m.