Triple

T3135078
Position Surface form Disambiguated ID Type / Status
Subject Aguascalientes E65507 entity
Predicate hasMunicipality P847 FINISHED
Object Jesús María
Jesús María is a municipality in the Mexican state of Aguascalientes, known for its growing urban area and integration into the metropolitan region of the state capital.
E328847 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: Jesús María | Statement: [Aguascalientes, hasMunicipality, Jesús María]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jesús María
Context triple: [Aguascalientes, hasMunicipality, Jesús María]
  • A. Jesús María
    Jesús María is a small city in central Argentina known for its traditional folklore and horse-taming festival.
  • B. José
    José is the given first name of Major League Baseball manager and former player Alex Cora.
  • C. José
    José is the given first name of former Major League Baseball player and coach Joey Cora.
  • D. Juan Diego
    Juan Diego is the 16th-century indigenous Mexican Catholic saint who reported the apparitions of Our Lady of Guadalupe, a pivotal event in Mexican religious history.
  • E. Gregorio
    Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
  • 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: Jesús María
Triple: [Aguascalientes, hasMunicipality, Jesús María]
Generated description
Jesús María is a municipality in the Mexican state of Aguascalientes, known for its growing urban area and integration into the metropolitan region of the state capital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jesús María
Target entity description: Jesús María is a municipality in the Mexican state of Aguascalientes, known for its growing urban area and integration into the metropolitan region of the state capital.
  • A. Jesús María
    Jesús María is a small city in central Argentina known for its traditional folklore and horse-taming festival.
  • B. José
    José is the given first name of Major League Baseball manager and former player Alex Cora.
  • C. José
    José is the given first name of former Major League Baseball player and coach Joey Cora.
  • D. Juan Diego
    Juan Diego is the 16th-century indigenous Mexican Catholic saint who reported the apparitions of Our Lady of Guadalupe, a pivotal event in Mexican religious history.
  • E. Gregorio
    Gregorio is a masculine given name of Latin origin, commonly used in Spanish and Italian-speaking cultures and derived from the name Gregory.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5637de0819089393429c4017298 completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f8793488190aa31040edaf1d627 completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2103d83688190b107ecbacac604c1 completed March 12, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69b210a290088190aaa10a015519e1de completed March 12, 2026, 1:02 a.m.
Created at: March 8, 2026, 3:05 p.m.