Triple

T9450156
Position Surface form Disambiguated ID Type / Status
Subject Ōita Prefecture E227866 entity
Predicate contains P35 FINISHED
Object Saiki
Saiki is a coastal city in southern Ōita Prefecture, Japan, known for its fishing industry and scenic seaside landscapes.
 E944335 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: Saiki | Statement: [Ōita Prefecture, contains, Saiki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saiki
Context triple: [Ōita Prefecture, contains, Saiki]
  • A. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • B. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • C. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • D. Inuyama
    Inuyama is a historic Japanese city in Aichi Prefecture best known for Inuyama Castle, one of Japan’s oldest surviving wooden castles, and its traditional cormorant fishing on the Kiso River.
  • E. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • 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: Saiki
Triple: [Ōita Prefecture, contains, Saiki]
Generated description
Saiki is a coastal city in southern Ōita Prefecture, Japan, known for its fishing industry and scenic seaside landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saiki
Target entity description: Saiki is a coastal city in southern Ōita Prefecture, Japan, known for its fishing industry and scenic seaside landscapes.
  • A. Fujieda
    Fujieda is a city in Shizuoka Prefecture, Japan, known as a regional commercial center with a mix of residential areas, agriculture, and light industry.
  • B. Yawata
    Yawata is a city in Japan known for its historic Iwashimizu Hachimangū Shrine and its location in the southern part of Kyoto Prefecture.
  • C. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • D. Inuyama
    Inuyama is a historic Japanese city in Aichi Prefecture best known for Inuyama Castle, one of Japan’s oldest surviving wooden castles, and its traditional cormorant fishing on the Kiso River.
  • E. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • 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_69ca8439f8bc8190997f2ef40c9f0bc2 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f6649a48190b6844daa6202efe5 completed April 1, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69f018324bf88190bcd2bf168b1065d3 completed April 28, 2026, 2:15 a.m.
NEDg Description generation batch_69f01d7ab930819095eaae226ab55b80 completed April 28, 2026, 2:37 a.m.
NED2 Entity disambiguation (via description) batch_69f043ddbfe481908e0c439dbd3e944f completed April 28, 2026, 5:21 a.m.
Created at: March 30, 2026, 7:51 p.m.