Triple

T1850310
Position Surface form Disambiguated ID Type / Status
Subject Gregorio Aglipay E41379 entity
Predicate givenName P17 FINISHED
Object Gregorio
Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
 E229139 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: Gregorio | Statement: [Gregorio Aglipay, givenName, Gregorio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gregorio
Context triple: [Gregorio Aglipay, givenName, Gregorio]
  • A. Timoteo
    Timoteo is a masculine given name, commonly used in Romance-language countries, derived from the biblical name Timothy.
  • B. Cipriano
    Cipriano is a masculine given name of Spanish origin, historically borne by figures such as the Protestant reformer and Bible translator Cipriano de Valera.
  • C. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • D. Julián
    Julián is a given name of Latin origin, commonly used in Spanish-speaking countries as a variant of Julian.
  • E. Vicente
    Vicente is a given name, common in Spanish- and Portuguese-speaking countries, that corresponds to the English name Vincent.
  • 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: Gregorio
Triple: [Gregorio Aglipay, givenName, Gregorio]
Generated description
Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gregorio
Target entity description: Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
  • A. Timoteo
    Timoteo is a masculine given name, commonly used in Romance-language countries, derived from the biblical name Timothy.
  • B. Cipriano
    Cipriano is a masculine given name of Spanish origin, historically borne by figures such as the Protestant reformer and Bible translator Cipriano de Valera.
  • C. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • D. Julián
    Julián is a given name of Latin origin, commonly used in Spanish-speaking countries as a variant of Julian.
  • E. Vicente
    Vicente is a given name, common in Spanish- and Portuguese-speaking countries, that corresponds to the English name Vincent.
  • 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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb066bd6881909c8d6a6b63cb0ee5 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fc7f4988190931e58d2f95b9049 completed March 9, 2026, 1:18 a.m.
NEDg Description generation batch_69ae2078f5bc81909e4226e4f4188e87 completed March 9, 2026, 1:20 a.m.
NED2 Entity disambiguation (via description) batch_69ae2121a43481908ea6eef3d4e06407 completed March 9, 2026, 1:23 a.m.
Created at: March 4, 2026, 7:33 p.m.