Triple

T10832896
Position Surface form Disambiguated ID Type / Status
Subject Omar Giménez E255667 entity
Predicate hasFamilyName P18 FINISHED
Object Giménez
Giménez is a Spanish-language surname commonly found in Spain and Latin American countries, borne by various notable figures in sports, arts, and public life.
 E888296 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: Giménez | Statement: [Omar Giménez, hasFamilyName, Giménez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Giménez
Context triple: [Omar Giménez, hasFamilyName, Giménez]
  • A. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • B. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • C. Diéguez
    Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
  • D. Echeandía
    Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
  • E. Quiñones
    Quiñones is a Spanish surname of noble origin historically associated with prominent political, military, and aristocratic families in Spain.
  • 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: Giménez
Triple: [Omar Giménez, hasFamilyName, Giménez]
Generated description
Giménez is a Spanish-language surname commonly found in Spain and Latin American countries, borne by various notable figures in sports, arts, and public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Giménez
Target entity description: Giménez is a Spanish-language surname commonly found in Spain and Latin American countries, borne by various notable figures in sports, arts, and public life.
  • A. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • B. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • C. Diéguez
    Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
  • D. Echeandía
    Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
  • E. Quiñones
    Quiñones is a Spanish surname of noble origin historically associated with prominent political, military, and aristocratic families in Spain.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7442439dc8190af59f9c8d0637c01 completed April 9, 2026, 6:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69de85aa5ea88190ab6399e46eba5c49 completed April 14, 2026, 6:21 p.m.
NEDg Description generation batch_69de8e70da448190b80068fea047a88c completed April 14, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69de94dd45548190a88b5ab991756d12 completed April 14, 2026, 7:26 p.m.
Created at: April 8, 2026, 9:19 p.m.