Triple

T8776027
Position Surface form Disambiguated ID Type / Status
Subject Spanish Town, Jamaica E208585 entity
Predicate formerName P65 FINISHED
Object Santiago de la Vega
Santiago de la Vega was the original Spanish colonial settlement that later became known as Spanish Town, a historic former capital of Jamaica.
 E756377 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: Santiago de la Vega | Statement: [Spanish Town, Jamaica, formerName, Santiago de la Vega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Santiago de la Vega
Context triple: [Spanish Town, Jamaica, formerName, Santiago de la Vega]
  • A. San Martín de la Vega
    San Martín de la Vega is a municipality in the Community of Madrid, Spain, known for hosting the Parque Warner Madrid theme park.
  • B. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • C. San Borja
    San Borja is a town in Bolivia’s Beni Department, known as a regional center in the country’s northern lowlands.
  • D. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • E. La Vega
    La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
  • 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: Santiago de la Vega
Triple: [Spanish Town, Jamaica, formerName, Santiago de la Vega]
Generated description
Santiago de la Vega was the original Spanish colonial settlement that later became known as Spanish Town, a historic former capital of Jamaica.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Santiago de la Vega
Target entity description: Santiago de la Vega was the original Spanish colonial settlement that later became known as Spanish Town, a historic former capital of Jamaica.
  • A. San Martín de la Vega
    San Martín de la Vega is a municipality in the Community of Madrid, Spain, known for hosting the Parque Warner Madrid theme park.
  • B. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • C. San Borja
    San Borja is a town in Bolivia’s Beni Department, known as a regional center in the country’s northern lowlands.
  • D. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • E. La Vega
    La Vega is a town and municipality in Colombia known for its lush mountainous landscapes and proximity to Bogotá.
  • 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_69ca835fbee88190bf625939bac48d7f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f5086088190b317cf2aac7bee83 completed March 31, 2026, 11:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51ceee2c81908d521cc4931e25dd completed April 3, 2026, 5:36 a.m.
NEDg Description generation batch_69cf53a27e2c8190a639d3b1007c11c3 completed April 3, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cf54129d888190b61d67f99ad36cb8 completed April 3, 2026, 5:45 a.m.
Created at: March 30, 2026, 6:42 p.m.