Triple

T14761505
Position Surface form Disambiguated ID Type / Status
Subject José María Bocanegra E346871 entity
Predicate familyName P18 FINISHED
Object Bocanegra
Bocanegra is a Spanish-origin surname borne by various notable figures, including Mexican politician and brief interim president José María Bocanegra.
 E1118865 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: Bocanegra | Statement: [José María Bocanegra, familyName, Bocanegra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bocanegra
Context triple: [José María Bocanegra, familyName, Bocanegra]
  • A. La Vega
    La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
  • B. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • C. La Barra
    La Barra is the natural volcanic reef that shelters Las Canteras Beach in Las Palmas de Gran Canaria, creating its calm, protected waters.
  • D. La Barra
    La Barra is a popular seaside resort town in Uruguay known for its beaches, nightlife, and proximity to Punta del Este.
  • E. Barra Vieja
    Barra Vieja is a coastal village and beach area near Acapulco in the Mexican state of Guerrero, known for its long sandy shoreline and seafood restaurants.
  • 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: Bocanegra
Triple: [José María Bocanegra, familyName, Bocanegra]
Generated description
Bocanegra is a Spanish-origin surname borne by various notable figures, including Mexican politician and brief interim president José María Bocanegra.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bocanegra
Target entity description: Bocanegra is a Spanish-origin surname borne by various notable figures, including Mexican politician and brief interim president José María Bocanegra.
  • A. La Vega
    La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
  • B. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • C. La Barra
    La Barra is the natural volcanic reef that shelters Las Canteras Beach in Las Palmas de Gran Canaria, creating its calm, protected waters.
  • D. La Barra
    La Barra is a popular seaside resort town in Uruguay known for its beaches, nightlife, and proximity to Punta del Este.
  • E. Barra Vieja
    Barra Vieja is a coastal village and beach area near Acapulco in the Mexican state of Guerrero, known for its long sandy shoreline and seafood restaurants.
  • 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_69d822e8896c819091169882f9b20486 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7f207dc819088a53f717736a121 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cf24c0081909221cb7d761e882f completed May 8, 2026, 4:18 p.m.
NEDg Description generation batch_69fe1913f01c8190917992cbcb8f0b62 completed May 8, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_69fe19c36dcc8190a8b3565d6e9cec04 completed May 8, 2026, 5:13 p.m.
Created at: April 10, 2026, 1:30 a.m.