Triple

T7233417
Position Surface form Disambiguated ID Type / Status
Subject Mexico City Metro Line 1 E154957 entity
Predicate hasStation P35 FINISHED
Object Balbuena
Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
 E651883 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: Balbuena | Statement: [Mexico City Metro Line 1, hasStation, Balbuena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Balbuena
Context triple: [Mexico City Metro Line 1, hasStation, Balbuena]
  • A. Baquero
    Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
  • B. Espinosa
    Espinosa is a neighborhood (barrio) within the municipality of Dorado in Puerto Rico.
  • C. Davila
    Davila is an Italian surname most notably associated with the 17th-century historian Enrico Caterino Davila.
  • D. Carabajal
    Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
  • E. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • 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: Balbuena
Triple: [Mexico City Metro Line 1, hasStation, Balbuena]
Generated description
Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Balbuena
Target entity description: Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • A. Baquero
    Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
  • B. Espinosa
    Espinosa is a neighborhood (barrio) within the municipality of Dorado in Puerto Rico.
  • C. Davila
    Davila is an Italian surname most notably associated with the 17th-century historian Enrico Caterino Davila.
  • D. Carabajal
    Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
  • E. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea11b03c81909702ad2e0c29758a completed March 27, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d38b5ac4819083837b149ec9e3ea completed March 28, 2026, 1:11 p.m.
NEDg Description generation batch_69c7d4319a308190aced214537d9a932 completed March 28, 2026, 1:14 p.m.
NED2 Entity disambiguation (via description) batch_69c7d4afddb88190ad24b66be8e6bc8a completed March 28, 2026, 1:16 p.m.
Created at: March 27, 2026, 2:55 p.m.