Triple

T6091669
Position Surface form Disambiguated ID Type / Status
Subject García E135778 entity
Predicate hasNotableBearer P458 FINISHED
Object Elena García
Elena García is a common Spanish personal name shared by multiple notable individuals across fields such as science, arts, and public life.
E620707 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: Elena García | Statement: [García, hasNotableBearer, Elena García]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elena García
Context triple: [García, hasNotableBearer, Elena García]
  • A. Elena Ruiz
    Elena Ruiz is a film editor best known for her work on the acclaimed Spanish horror film "The Orphanage."
  • B. María García
    María García is a widely occurring Spanish personal name shared by numerous women across Spanish-speaking countries, making it one of the most common Hispanic name combinations.
  • C. Lucía García
    Lucía García is a Spanish professional footballer known for playing as a forward for top clubs and the Spain women’s national team.
  • D. Rosa García
    Rosa García is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname García.
  • E. Elena Alvarez
    Elena Alvarez is a socially conscious, feminist teenage daughter in the Cuban-American family at the heart of the sitcom "One Day at a Time" (2017).
  • 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: Elena García
Triple: [García, hasNotableBearer, Elena García]
Generated description
Elena García is a common Spanish personal name shared by multiple notable individuals across fields such as science, arts, and public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elena García
Target entity description: Elena García is a common Spanish personal name shared by multiple notable individuals across fields such as science, arts, and public life.
  • A. Elena Ruiz
    Elena Ruiz is a film editor best known for her work on the acclaimed Spanish horror film "The Orphanage."
  • B. María García
    María García is a widely occurring Spanish personal name shared by numerous women across Spanish-speaking countries, making it one of the most common Hispanic name combinations.
  • C. Lucía García
    Lucía García is a Spanish professional footballer known for playing as a forward for top clubs and the Spain women’s national team.
  • D. Rosa García
    Rosa García is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname García.
  • E. Elena Alvarez
    Elena Alvarez is a socially conscious, feminist teenage daughter in the Cuban-American family at the heart of the sitcom "One Day at a Time" (2017).
  • 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_69c0087cd3c48190b459848c72d84eb1 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c057ab7324819086d4708e6f9391c0 completed March 22, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a5979208190b3bedb6234181245 completed March 28, 2026, 12:01 a.m.
NEDg Description generation batch_69c71c8f0e6081908a59f0c6ebbe5927 completed March 28, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_69c71f6346108190b13802a2cca38263 completed March 28, 2026, 12:22 a.m.
Created at: March 22, 2026, 4:12 p.m.