Triple

T414914
Position Surface form Disambiguated ID Type / Status
Subject Giulino di Mezzegra E9570 entity
Predicate locatedNear P294 FINISHED
Object Dongo
Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
 E54844 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: Dongo | Statement: [Giulino di Mezzegra, locatedNear, Dongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dongo
Context triple: [Giulino di Mezzegra, locatedNear, Dongo]
  • A. Canino
    Canino is a small town in the Lazio region of central Italy, historically notable as the birthplace of Pope Paul III.
  • B. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • C. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • D. Myene
    Myene is a Bantu language spoken primarily by the Myene people along Gabon’s Atlantic coast and recognized as one of the country’s main national languages.
  • E. Ngozi
    Ngozi is a Nigerian given name of Igbo origin commonly used for females and meaning "blessing."
  • 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: Dongo
Triple: [Giulino di Mezzegra, locatedNear, Dongo]
Generated description
Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dongo
Target entity description: Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • A. Canino
    Canino is a small town in the Lazio region of central Italy, historically notable as the birthplace of Pope Paul III.
  • B. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • C. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • D. Myene
    Myene is a Bantu language spoken primarily by the Myene people along Gabon’s Atlantic coast and recognized as one of the country’s main national languages.
  • E. Ngozi
    Ngozi is a Nigerian given name of Igbo origin commonly used for females and meaning "blessing."
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ee8d835881908403ea23901e52b3 completed Feb. 28, 2026, 1:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69a431dd98dc8190a0020cdbeec5cfbf completed March 1, 2026, 12:32 p.m.
NEDg Description generation batch_69a43267c1d081908b2036402ce0ec11 completed March 1, 2026, 12:34 p.m.
NED2 Entity disambiguation (via description) batch_69a432f94a948190a958bba70c2fc806 completed March 1, 2026, 12:37 p.m.
Created at: Feb. 28, 2026, 1:09 p.m.