Triple

T10014933
Position Surface form Disambiguated ID Type / Status
Subject Aichi Prefecture E199464 entity
Predicate containsCity P294 FINISHED
Object Kitanagoya
Kitanagoya is a city in central Japan known as a residential and commercial suburb within the Nagoya metropolitan area.
 E992194 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: Kitanagoya | Statement: [Aichi Prefecture, containsCity, Kitanagoya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kitanagoya
Context triple: [Aichi Prefecture, containsCity, Kitanagoya]
  • A. Kyotanabe
    Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
  • B. Izumisano
    Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
  • C. Kameoka
    Kameoka is a city in Kyoto Prefecture, Japan, known for its rural landscapes, historical sites, and proximity to Kyoto.
  • D. Hikone
    Hikone is a historic city in Shiga Prefecture, Japan, best known for its well-preserved Hikone Castle overlooking Lake Biwa.
  • E. Kawagoe
    Kawagoe is a historic Japanese city in Saitama Prefecture, often called "Little Edo" for its well-preserved Edo-period streetscapes and traditional warehouses.
  • 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: Kitanagoya
Triple: [Aichi Prefecture, containsCity, Kitanagoya]
Generated description
Kitanagoya is a city in central Japan known as a residential and commercial suburb within the Nagoya metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kitanagoya
Target entity description: Kitanagoya is a city in central Japan known as a residential and commercial suburb within the Nagoya metropolitan area.
  • A. Kyotanabe
    Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
  • B. Izumisano
    Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
  • C. Kameoka
    Kameoka is a city in Kyoto Prefecture, Japan, known for its rural landscapes, historical sites, and proximity to Kyoto.
  • D. Hikone
    Hikone is a historic city in Shiga Prefecture, Japan, best known for its well-preserved Hikone Castle overlooking Lake Biwa.
  • E. Kawagoe
    Kawagoe is a historic Japanese city in Saitama Prefecture, often called "Little Edo" for its well-preserved Edo-period streetscapes and traditional warehouses.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd49b19c8190b429e3533d072648 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69f65e9136bc8190b35685376da7007e completed May 2, 2026, 8:29 p.m.
NEDg Description generation batch_69f660bc541c8190a4d1d7a4cc959ecf completed May 2, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_69f6617997188190bfce14c54619af7f completed May 2, 2026, 8:41 p.m.
Created at: March 30, 2026, 8:52 p.m.