Triple

T7958566
Position Surface form Disambiguated ID Type / Status
Subject Caquetá Department E184801 entity
Predicate containsMunicipality P852 FINISHED
Object Milan
Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
 E704661 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: Milan | Statement: [Caquetá Department, containsMunicipality, Milan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Milan
Context triple: [Caquetá Department, containsMunicipality, Milan]
  • A. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • B. Milan
    Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • C. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • D. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • E. Turin
    Turin is a major city in northern Italy known for its rich history, Baroque architecture, automotive industry, and role as a cultural and economic hub.
  • 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: Milan
Triple: [Caquetá Department, containsMunicipality, Milan]
Generated description
Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Milan
Target entity description: Milan is a municipality located in Colombia’s Caquetá Department, within the Amazonian region of the country.
  • A. Milan
    Milan is a major Italian metropolis renowned as a global center for fashion, design, finance, and culture.
  • B. Milan
    Milan is a village in northern Ohio best known as the birthplace of inventor Thomas Edison and for its historic canal-era architecture.
  • C. Milan
    Milan is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • D. Milano
    Milano is a popular line of chocolate-filled sandwich cookies produced by Pepperidge Farm, a subsidiary of Campbell Soup Company.
  • E. Turin
    Turin is a small town located in Coweta County in the U.S. state of Georgia.
  • 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_69ca8293a2388190aace944d7ed9c0c0 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b80050c81909b2db95ade495052 completed March 31, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbdee8da948190b593f855a09260a1 completed March 31, 2026, 2:49 p.m.
NEDg Description generation batch_69cc46c11e68819087f5083bb85ec7ab completed March 31, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc47fa1524819089ef5b3f8bf7f670 completed March 31, 2026, 10:17 p.m.
Created at: March 30, 2026, 5:11 p.m.