Triple

T2881841
Position Surface form Disambiguated ID Type / Status
Subject Colombian Amazon region E59413 entity
Predicate majorCity P316 FINISHED
Object Leticia
Leticia is a remote Colombian city on the Amazon River, known as a key gateway to the Amazon rainforest and a tri-border point with Brazil and Peru.
 E307981 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: Leticia | Statement: [Colombian Amazon region, majorCity, Leticia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Leticia
Context triple: [Colombian Amazon region, majorCity, Leticia]
  • A. Lorena
    Lorena is a city in the state of São Paulo, Brazil, known for hosting a campus of the University of São Paulo.
  • B. Paola
    Paola is a town in southeastern Malta known for its historic sites, including the prehistoric Ħal Saflieni Hypogeum and other cultural landmarks.
  • C. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • D. Djanira
    Djanira was a prominent Brazilian modernist painter known for her vivid depictions of everyday life, religious themes, and popular culture.
  • E. Madalena
    Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
  • 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: Leticia
Triple: [Colombian Amazon region, majorCity, Leticia]
Generated description
Leticia is a remote Colombian city on the Amazon River, known as a key gateway to the Amazon rainforest and a tri-border point with Brazil and Peru.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Leticia
Target entity description: Leticia is a remote Colombian city on the Amazon River, known as a key gateway to the Amazon rainforest and a tri-border point with Brazil and Peru.
  • A. Lorena
    Lorena is a city in the state of São Paulo, Brazil, known for hosting a campus of the University of São Paulo.
  • B. Paola
    Paola is a town in southeastern Malta known for its historic sites, including the prehistoric Ħal Saflieni Hypogeum and other cultural landmarks.
  • C. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • D. Djanira
    Djanira was a prominent Brazilian modernist painter known for her vivid depictions of everyday life, religious themes, and popular culture.
  • E. Madalena
    Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe02aa5948190a2e0bd9168232bd5 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b031633efc819088c2ea29eafaff0f completed March 10, 2026, 2:57 p.m.
NEDg Description generation batch_69b033894ca881908691b88e6108257c completed March 10, 2026, 3:06 p.m.
NED2 Entity disambiguation (via description) batch_69b03c3af7b48190b66bb32df59196e3 completed March 10, 2026, 3:43 p.m.
Created at: March 6, 2026, 10:03 p.m.