Triple

T6116973
Position Surface form Disambiguated ID Type / Status
Subject Kizugawa E136382 entity
Predicate borderedBy P224 FINISHED
Object Kasagi
Kasagi is a small town in Kyoto Prefecture, Japan, known for its scenic river landscapes and historic temples.
 E622952 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: Kasagi | Statement: [Kizugawa, borderedBy, Kasagi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kasagi
Context triple: [Kizugawa, borderedBy, Kasagi]
  • A. Kogarah
    Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
  • B. Koga
    Koga is a coastal city in Japan known as a residential suburb of Fukuoka with convenient access to the greater Fukuoka metropolitan area.
  • C. Togoshi
    Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
  • D. Kokane
    Kokane is an American rapper and singer known for his distinctive G-funk style and frequent collaborations with West Coast hip hop artists.
  • E. Koromo
    Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
  • 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: Kasagi
Triple: [Kizugawa, borderedBy, Kasagi]
Generated description
Kasagi is a small town in Kyoto Prefecture, Japan, known for its scenic river landscapes and historic temples.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kasagi
Target entity description: Kasagi is a small town in Kyoto Prefecture, Japan, known for its scenic river landscapes and historic temples.
  • A. Kogarah
    Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
  • B. Koga
    Koga is a coastal city in Japan known as a residential suburb of Fukuoka with convenient access to the greater Fukuoka metropolitan area.
  • C. Togoshi
    Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
  • D. Kokane
    Kokane is an American rapper and singer known for his distinctive G-funk style and frequent collaborations with West Coast hip hop artists.
  • E. Koromo
    Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
  • 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05beb4cfc8190ab67a5338ec59cea completed March 22, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f6514948190a5562201e7b36e27 completed March 28, 2026, 1:31 a.m.
NEDg Description generation batch_69c7304c0bac8190a9ece4e50ab49586 completed March 28, 2026, 1:35 a.m.
NED2 Entity disambiguation (via description) batch_69c7310fa9bc8190bfb0a43890dc5e96 completed March 28, 2026, 1:38 a.m.
Created at: March 22, 2026, 4:14 p.m.