Triple

T2262850
Position Surface form Disambiguated ID Type / Status
Subject Monica De La Cruz E50076 entity
Predicate familyName P18 FINISHED
Object De La Cruz
De La Cruz is a Hispanic surname commonly found in Spanish-speaking communities and among people of Latin American descent.
E251769 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 La Cruz | Statement: [Monica De La Cruz, familyName, De La Cruz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De La Cruz
Context triple: [Monica De La Cruz, familyName, De La Cruz]
  • A. Rojas
    Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
  • B. Antonio Cruz Villalón
    Antonio Cruz Villalón is a Spanish architect best known as a co-founder of the renowned architectural firm Cruz y Ortiz Arquitectos, recognized for its contemporary public and cultural buildings.
  • 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. Magaña
    Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
  • E. Sosa
    Sosa is a Spanish-origin surname most famously associated with former Major League Baseball slugger Sammy Sosa.
  • 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 La Cruz
Triple: [Monica De La Cruz, familyName, De La Cruz]
Generated description
De La Cruz is a Hispanic surname commonly found in Spanish-speaking communities and among people of Latin American descent.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: De La Cruz
Target entity description: De La Cruz is a Hispanic surname commonly found in Spanish-speaking communities and among people of Latin American descent.
  • A. Rojas
    Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
  • B. Antonio Cruz Villalón
    Antonio Cruz Villalón is a Spanish architect best known as a co-founder of the renowned architectural firm Cruz y Ortiz Arquitectos, recognized for its contemporary public and cultural buildings.
  • 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. Magaña
    Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
  • E. Sosa
    Sosa is a Spanish-origin surname most famously associated with former Major League Baseball slugger Sammy Sosa.
  • 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_69a88b01e0048190ba96431b5f990ba9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc18be8308190abc4a59d37dfd93a completed March 7, 2026, 6:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71cfd3b08190988474aa0fa985fe completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae7688583c8190abb05be41103762a completed March 9, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_69ae76ec3c0c8190bfb7d25b435c777f completed March 9, 2026, 7:29 a.m.
Created at: March 4, 2026, 7:48 p.m.