Triple

T2881844
Position Surface form Disambiguated ID Type / Status
Subject Colombian Amazon region E59413 entity
Predicate majorCity P316 FINISHED
Object Mitú
Mitú is a remote Colombian town that serves as the capital of the Vaupés Department in the Amazon rainforest, known for its indigenous communities and dense jungle surroundings.
 E307984 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: Mitú | Statement: [Colombian Amazon region, majorCity, Mitú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mitú
Context triple: [Colombian Amazon region, majorCity, Mitú]
  • A. Mogotón
    Mogotón is a mountain on the border between Nicaragua and Honduras that forms the highest peak in Nicaragua.
  • B. Mishanya
    Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
  • C. Mariquita
    Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
  • D. Naranjito
    Naranjito is a municipality located in the central region of Puerto Rico, known for its mountainous terrain and agricultural traditions.
  • E. Naranjito
    Naranjito is the smiling orange cartoon character that served as the official mascot of the 1982 FIFA World Cup held in Spain.
  • 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: Mitú
Triple: [Colombian Amazon region, majorCity, Mitú]
Generated description
Mitú is a remote Colombian town that serves as the capital of the Vaupés Department in the Amazon rainforest, known for its indigenous communities and dense jungle surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mitú
Target entity description: Mitú is a remote Colombian town that serves as the capital of the Vaupés Department in the Amazon rainforest, known for its indigenous communities and dense jungle surroundings.
  • A. Mogotón
    Mogotón is a mountain on the border between Nicaragua and Honduras that forms the highest peak in Nicaragua.
  • B. Mishanya
    Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
  • C. Mariquita
    Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
  • D. Naranjito
    Naranjito is a municipality located in the central region of Puerto Rico, known for its mountainous terrain and agricultural traditions.
  • E. Naranjito
    Naranjito is the smiling orange cartoon character that served as the official mascot of the 1982 FIFA World Cup held in Spain.
  • 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.