Triple

T7975625
Position Surface form Disambiguated ID Type / Status
Subject Santiago E185438 entity
Predicate hasVariant P455 FINISHED
Object Yago
Yago is a given name, often used as a variant of Santiago in Spanish- and Portuguese-speaking contexts.
 E703075 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: Yago | Statement: [Santiago, hasVariant, Yago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yago
Context triple: [Santiago, hasVariant, Yago]
  • A. Norberto
    Norberto is an Italian given name most notably borne by the influential legal and political philosopher Norberto Bobbio.
  • B. Marcelo
    Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
  • C. Jorge
    Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
  • D. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • E. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • 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: Yago
Triple: [Santiago, hasVariant, Yago]
Generated description
Yago is a given name, often used as a variant of Santiago in Spanish- and Portuguese-speaking contexts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yago
Target entity description: Yago is a given name, often used as a variant of Santiago in Spanish- and Portuguese-speaking contexts.
  • A. Norberto
    Norberto is an Italian given name most notably borne by the influential legal and political philosopher Norberto Bobbio.
  • B. Marcelo
    Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
  • C. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • D. Jorge
    Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
  • E. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • 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_69ca829851908190b4e03829353ee7c3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bf56f688190902b95afe42635ec completed March 31, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0c39e248190a146c1f2fd815f26 completed March 31, 2026, 2:57 p.m.
NEDg Description generation batch_69cbe43d29f8819080f7d729c4f28c75 completed March 31, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69cc32e2e1c48190b86218bff9af99f5 completed March 31, 2026, 8:47 p.m.
Created at: March 30, 2026, 5:14 p.m.