Triple

T1178180
Position Surface form Disambiguated ID Type / Status
Subject Moriguchi E25075 entity
Predicate locatedNear P294 FINISHED
Object Kadoma
Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
 E134780 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: Kadoma | Statement: [Moriguchi, locatedNear, Kadoma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kadoma
Context triple: [Moriguchi, locatedNear, Kadoma]
  • A. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • B. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • C. Mbare
    Mbare is one of the oldest and most densely populated townships in Harare, Zimbabwe, known as a major transport hub and bustling market area.
  • D. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • E. Nairobi
    Nairobi is a fan-favorite character from the Spanish series "Money Heist," known for her sharp leadership, optimism, and expertise in overseeing the gang’s money-printing operations.
  • 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: Kadoma
Triple: [Moriguchi, locatedNear, Kadoma]
Generated description
Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kadoma
Target entity description: Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
  • A. Kisumu
    Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
  • B. Dodoma
    Dodoma is the political and administrative capital city of Tanzania, located in the country’s central region.
  • C. Mbare
    Mbare is one of the oldest and most densely populated townships in Harare, Zimbabwe, known as a major transport hub and bustling market area.
  • D. Nairobi
    Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
  • E. Nairobi
    Nairobi is a fan-favorite character from the Spanish series "Money Heist," known for her sharp leadership, optimism, and expertise in overseeing the gang’s money-printing operations.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd10ccc481908d5bcef648aab3c1 completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6f1cab308190bdb5ae1e01d83b61 completed March 7, 2026, 6:31 p.m.
NEDg Description generation batch_69ac6ff4c62881908cf88169e99d2983 completed March 7, 2026, 6:35 p.m.
NED2 Entity disambiguation (via description) batch_69ac704cdaf08190b77b0b9345537d84 completed March 7, 2026, 6:37 p.m.
Created at: March 1, 2026, 7:45 p.m.