Triple

T1215367
Position Surface form Disambiguated ID Type / Status
Subject Alfonso Salmerón E26095 entity
Predicate givenName P17 FINISHED
Object Alfonso
Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
 E162427 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: Alfonso | Statement: [Alfonso Salmerón, givenName, Alfonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alfonso
Context triple: [Alfonso Salmerón, givenName, Alfonso]
  • A. Manuel
    Manuel is the given name of Manny Ramirez, the former Major League Baseball star known for his powerful hitting and tenure with the Boston Red Sox.
  • B. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • C. Ferdinand
    Ferdinand is a masculine given name of Germanic origin historically borne by numerous European nobles and monarchs.
  • D. Luís
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • E. Carlos
    Carlos is a common Spanish given name widely used across Spanish-speaking countries and communities.
  • 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: Alfonso
Triple: [Alfonso Salmerón, givenName, Alfonso]
Generated description
Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alfonso
Target entity description: Alfonso is a masculine given name of Spanish and Italian origin historically borne by numerous kings, nobles, and notable figures across Europe.
  • A. Manuel
    Manuel is the given name of Manny Ramirez, the former Major League Baseball star known for his powerful hitting and tenure with the Boston Red Sox.
  • B. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • C. Ferdinand
    Ferdinand is a masculine given name of Germanic origin historically borne by numerous European nobles and monarchs.
  • D. Luís
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • E. Carlos
    Carlos is a common Spanish given name widely used across Spanish-speaking countries and communities.
  • 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_69a4948331fc8190b531ac9bec71c491 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be0370b4819093618930f4eecfcc completed March 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace55382c88190b838478f3c178c2d completed March 8, 2026, 2:56 a.m.
NEDg Description generation batch_69ace5fb515081908acadef0303b8f6e completed March 8, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69ace9ba4b3481908d03636d8f72d04c completed March 8, 2026, 3:15 a.m.
Created at: March 1, 2026, 7:46 p.m.