Triple

T621149
Position Surface form Disambiguated ID Type / Status
Subject Arsenio Linares y Pombo E14515 entity
Predicate givenName P17 FINISHED
Object Arsenio
Arsenio is a masculine given name of Spanish origin, historically borne by several notable figures in Spanish-speaking countries.
 E83128 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: Arsenio | Statement: [Arsenio Linares y Pombo, givenName, Arsenio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Arsenio
Context triple: [Arsenio Linares y Pombo, givenName, Arsenio]
  • A. Antonio Trashorras
    Antonio Trashorras is a Spanish screenwriter best known for his work in horror cinema, including co-writing Guillermo del Toro’s acclaimed film "The Devil’s Backbone."
  • B. Ramón
    Ramón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • C. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • D. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • E. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • 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: Arsenio
Triple: [Arsenio Linares y Pombo, givenName, Arsenio]
Generated description
Arsenio is a masculine given name of Spanish origin, historically borne by several notable figures in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Arsenio
Target entity description: Arsenio is a masculine given name of Spanish origin, historically borne by several notable figures in Spanish-speaking countries.
  • A. Antonio Trashorras
    Antonio Trashorras is a Spanish screenwriter best known for his work in horror cinema, including co-writing Guillermo del Toro’s acclaimed film "The Devil’s Backbone."
  • B. Ramón
    Ramón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • C. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • D. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • E. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e3e5d80819096e72e11b533f931 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c38d2ee88190b577ca56b84e851e completed March 2, 2026, 5:06 p.m.
NEDg Description generation batch_69a5c51ae0cc8190b522436337980624 completed March 2, 2026, 5:12 p.m.
NED2 Entity disambiguation (via description) batch_69a5ce579ca8819084a1eae104e7058b completed March 2, 2026, 5:52 p.m.
Created at: March 1, 2026, 7:35 p.m.