Triple

T9196300
Position Surface form Disambiguated ID Type / Status
Subject Christopher E220717 entity
Predicate hasVariant P455 FINISHED
Object Cristóbal
Cristóbal is the Spanish given name equivalent to Christopher, commonly used in Spanish-speaking countries.
 E783721 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: Cristóbal | Statement: [Christopher, hasVariant, Cristóbal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cristóbal
Context triple: [Christopher, hasVariant, Cristóbal]
  • A. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • B. Colón
    Colón is a Spanish-origin surname commonly found in Hispanic communities and notably borne by figures such as comic book artist Ernie Colón.
  • C. Colón
    Colón is a riverside city in Argentina known for its tourism, hot springs, and access to the Uruguay River.
  • D. Colón
    Colón is a small municipality located in Colombia's southern Amazonian region within the Putumayo Department.
  • E. Colón
    Colón is a municipality and city in western Cuba known for its agricultural surroundings 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: Cristóbal
Triple: [Christopher, hasVariant, Cristóbal]
Generated description
Cristóbal is the Spanish given name equivalent to Christopher, commonly used in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cristóbal
Target entity description: Cristóbal is the Spanish given name equivalent to Christopher, commonly used in Spanish-speaking countries.
  • A. Guillermo
    Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
  • B. Colón
    Colón is a Spanish-origin surname commonly found in Hispanic communities and notably borne by figures such as comic book artist Ernie Colón.
  • C. Colón
    Colón is a riverside city in Argentina known for its tourism, hot springs, and access to the Uruguay River.
  • D. Colón
    Colón is a small municipality located in Colombia's southern Amazonian region within the Putumayo Department.
  • E. Colón
    Colón is a municipality and city in western Cuba known for its agricultural surroundings 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd87d6460819097234b5dd3f749b4 completed April 1, 2026, 8:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c36d7208190a593923bad3d18e7 completed April 4, 2026, 12:32 a.m.
NEDg Description generation batch_69d05cb45280819096747ff8f7d5c2a0 completed April 4, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69d05d5d29f4819081c28b24cb2058b0 completed April 4, 2026, 12:37 a.m.
Created at: March 30, 2026, 7:25 p.m.