Triple

T6888763
Position Surface form Disambiguated ID Type / Status
Subject Xenia E158990 entity
Predicate hasVariant P455 FINISHED
Object Xenia (Spanish form)
Xenia (Spanish form) is the Spanish-language variant of the feminine given name Xenia, used in Spanish-speaking countries.
 E625713 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: Xenia (Spanish form) | Statement: [Xenia, hasVariant, Xenia (Spanish form)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Xenia (Spanish form)
Context triple: [Xenia, hasVariant, Xenia (Spanish form)]
  • A. Marta (Spanish)
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • B. Alejandra
    Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
  • C. Amparo
    Amparo is a municipality in the interior of Brazil known for its historical architecture and role in the coffee-producing region of the state of São Paulo.
  • D. Fabiola
    Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
  • E. Begoña
    Begoña is a Spanish feminine given name commonly used in Spain and Spanish-speaking countries.
  • 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: Xenia (Spanish form)
Triple: [Xenia, hasVariant, Xenia (Spanish form)]
Generated description
Xenia (Spanish form) is the Spanish-language variant of the feminine given name Xenia, used in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Xenia (Spanish form)
Target entity description: Xenia (Spanish form) is the Spanish-language variant of the feminine given name Xenia, used in Spanish-speaking countries.
  • A. Marta (Spanish)
    Marta is the Spanish given name equivalent to Martha, commonly used in Spanish-speaking countries.
  • B. Alejandra
    Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
  • C. Amparo
    Amparo is a municipality in the interior of Brazil known for its historical architecture and role in the coffee-producing region of the state of São Paulo.
  • D. Fabiola
    Fabiola is a given name of Latin origin, historically associated with saints and European royalty.
  • E. Begoña
    Begoña is a Spanish feminine given name commonly used in Spain and Spanish-speaking countries.
  • 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_69c6883568c8819081db6407e892cccc completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d9101e30819084695ba0003a255c completed March 27, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c742e71bcc81908231a861be47b7db completed March 28, 2026, 2:54 a.m.
NEDg Description generation batch_69c744036378819083a3be5c50b189b2 completed March 28, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69c744eb1cf88190aaf90198d04d4500 completed March 28, 2026, 3:03 a.m.
Created at: March 27, 2026, 2:23 p.m.