Triple

T18600199
Position Surface form Disambiguated ID Type / Status
Subject 大分県 E454597 entity
Predicate 別名 P39 FINISHED
Object 豊の国
豊の国 is a traditional nickname for Japan’s Ōita Prefecture, evoking its historical prosperity and rich natural and cultural resources.
E1333469 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: 豊の国 | Statement: [大分県, 別名, 豊の国]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 豊の国
Context triple: [大分県, 別名, 豊の国]
  • A. Reihoku
    Reihoku is a coastal town located on the Amakusa Islands in Kumamoto Prefecture, Japan, known for its fishing industry and scenic seaside landscapes.
  • B. Settsu
    Settsu is a city in Osaka Prefecture, Japan, known as part of the Osaka metropolitan area.
  • C. Higashiyamato
    Higashiyamato is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama region’s parks and green spaces.
  • D. Ōshū
    Ōshū is a city in Japan’s Tōhoku region known for its rural landscapes, historical sites, and agricultural production.
  • E. Shinano
    Shinano was a Japanese World War II aircraft carrier, originally laid down as a Yamato-class battleship and notable for being the largest carrier ever sunk in combat.
  • 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: 豊の国
Triple: [大分県, 別名, 豊の国]
Generated description
豊の国 is a traditional nickname for Japan’s Ōita Prefecture, evoking its historical prosperity and rich natural and cultural resources.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 豊の国
Target entity description: 豊の国 is a traditional nickname for Japan’s Ōita Prefecture, evoking its historical prosperity and rich natural and cultural resources.
  • A. Reihoku
    Reihoku is a coastal town located on the Amakusa Islands in Kumamoto Prefecture, Japan, known for its fishing industry and scenic seaside landscapes.
  • B. Settsu
    Settsu is a city in Osaka Prefecture, Japan, known as part of the Osaka metropolitan area.
  • C. Higashiyamato
    Higashiyamato is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and proximity to the Tama region’s parks and green spaces.
  • D. Ōshū
    Ōshū is a city in Japan’s Tōhoku region known for its rural landscapes, historical sites, and agricultural production.
  • E. Shinano
    Shinano was a Japanese World War II aircraft carrier, originally laid down as a Yamato-class battleship and notable for being the largest carrier ever sunk in combat.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5475018548190a2f497081af7ce55 completed April 19, 2026, 9:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a050381bacc81909f416e8b9910f046 completed May 13, 2026, 11:04 p.m.
NEDg Description generation batch_6a0504ff8c6c8190a211b3f3e30229b4 completed May 13, 2026, 11:10 p.m.
NED2 Entity disambiguation (via description) batch_6a0505606bf88190afe635b2517d170b completed May 13, 2026, 11:12 p.m.
Created at: April 10, 2026, 11:45 a.m.