Triple

T5877758
Position Surface form Disambiguated ID Type / Status
Subject Ako E130667 entity
Predicate adjacentTo P224 FINISHED
Object Bizen
Bizen is a city in Okayama Prefecture, Japan, historically renowned for its traditional Bizen-yaki pottery.
 E553312 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: Bizen | Statement: [Ako, adjacentTo, Bizen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bizen
Context triple: [Ako, adjacentTo, Bizen]
  • A. Kakogawa
    Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
  • B. Tanabe
    Tanabe is a coastal city in Japan known as a gateway to the Kumano Kodo pilgrimage routes and for its scenic natural landscapes.
  • C. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • D. Kawanishi
    Kawanishi is a city in Hyōgo Prefecture, Japan, known as a residential and commuter town within the Osaka metropolitan area.
  • E. Sanuki
    Sanuki is a city in Kagawa Prefecture on Japan’s Shikoku island, known for its coastal scenery and association with Sanuki-style udon noodles.
  • 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: Bizen
Triple: [Ako, adjacentTo, Bizen]
Generated description
Bizen is a city in Okayama Prefecture, Japan, historically renowned for its traditional Bizen-yaki pottery.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bizen
Target entity description: Bizen is a city in Okayama Prefecture, Japan, historically renowned for its traditional Bizen-yaki pottery.
  • A. Kakogawa
    Kakogawa is an industrial and residential city in central Hyōgo Prefecture, Japan, known for its steel manufacturing and role as a regional transportation hub.
  • B. Tanabe
    Tanabe is a coastal city in Japan known as a gateway to the Kumano Kodo pilgrimage routes and for its scenic natural landscapes.
  • C. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • D. Kawanishi
    Kawanishi is a city in Hyōgo Prefecture, Japan, known as a residential and commuter town within the Osaka metropolitan area.
  • E. Sanuki
    Sanuki is a city in Kagawa Prefecture on Japan’s Shikoku island, known for its coastal scenery and association with Sanuki-style udon noodles.
  • 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_69c0085523688190bfd487479ce819e6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03630eefc8190ad1aaa1919ecf97f completed March 22, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b12861c081909f95f1ef6a1f457c completed March 23, 2026, 3:19 a.m.
NEDg Description generation batch_69c0b299fe78819089a2ca8a1ae44329 completed March 23, 2026, 3:25 a.m.
NED2 Entity disambiguation (via description) batch_69c0b2ea7e60819099417b5acb21f8d0 completed March 23, 2026, 3:26 a.m.
Created at: March 22, 2026, 3:57 p.m.