Triple

T905993
Position Surface form Disambiguated ID Type / Status
Subject José Antonio Echeverría E19549 entity
Predicate familyName P18 FINISHED
Object Echeverría
Echeverría is a Spanish-language surname borne by various notable figures in politics, literature, and the arts across the Spanish-speaking world.
 E116872 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: Echeverría | Statement: [José Antonio Echeverría, familyName, Echeverría]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Echeverría
Context triple: [José Antonio Echeverría, familyName, Echeverría]
  • A. Esquivel
    Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
  • B. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • C. Montero Ríos
    Montero Ríos is the surname of Eugenio Montero Ríos, a prominent Spanish jurist and politician who served as Prime Minister of Spain in the early 20th century.
  • D. Ovalle
    Ovalle is a Chilean city known as an agricultural and commercial center in the north-central part of the country.
  • E. Baquedano
    Baquedano is a major interchange station in the Santiago Metro system, serving as a key hub that connects multiple lines in central Santiago, Chile.
  • 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: Echeverría
Triple: [José Antonio Echeverría, familyName, Echeverría]
Generated description
Echeverría is a Spanish-language surname borne by various notable figures in politics, literature, and the arts across the Spanish-speaking world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Echeverría
Target entity description: Echeverría is a Spanish-language surname borne by various notable figures in politics, literature, and the arts across the Spanish-speaking world.
  • A. Esquivel
    Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
  • B. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • C. Montero Ríos
    Montero Ríos is the surname of Eugenio Montero Ríos, a prominent Spanish jurist and politician who served as Prime Minister of Spain in the early 20th century.
  • D. Ovalle
    Ovalle is a Chilean city known as an agricultural and commercial center in the north-central part of the country.
  • E. Baquedano
    Baquedano is a major interchange station in the Santiago Metro system, serving as a key hub that connects multiple lines in central Santiago, Chile.
  • 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_69a4939e889c8190ac148b3ac1a7f90b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2cc85a08190bc8186eb9ed1fa38 completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac257f3b2c819082a16c7242d89404 completed March 7, 2026, 1:17 p.m.
NEDg Description generation batch_69ac25e6cc608190a717c7991936c3a5 completed March 7, 2026, 1:19 p.m.
NED2 Entity disambiguation (via description) batch_69ac264b6bc08190a18c4f61ea6eb0f4 completed March 7, 2026, 1:21 p.m.
Created at: March 1, 2026, 7:39 p.m.