Triple

T5952158
Position Surface form Disambiguated ID Type / Status
Subject Hashimoto E132424 entity
Predicate hasNameInJapanese P28734 FINISHED
Object 橋本市
橋本市は、和歌山県北東部に位置し、高野山への玄関口として知られる都市です。
 E557896 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: 橋本市 | Statement: [Hashimoto, hasNameInJapanese, 橋本市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 橋本市
Context triple: [Hashimoto, hasNameInJapanese, 橋本市]
  • A. Nagaokakyo City
    Nagaokakyo City is a suburban city in Kyoto Prefecture, Japan, known for its residential communities, historical temples, and convenient rail access to Kyoto and Osaka.
  • B. Morioka
    Morioka is the capital city of Iwate Prefecture in Japan’s Tōhoku region, known for its historic castle site, surrounding mountains, and distinctive local noodle dishes.
  • C. Maebashi
    Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
  • D. Kanazawa
    Kanazawa is a historic Japanese city on the Sea of Japan coast, renowned for its well-preserved samurai and geisha districts, traditional crafts, and the celebrated Kenrokuen Garden.
  • E. Bunkyō City
    Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
  • 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: 橋本市
Triple: [Hashimoto, hasNameInJapanese, 橋本市]
Generated description
橋本市は、和歌山県北東部に位置し、高野山への玄関口として知られる都市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 橋本市
Target entity description: 橋本市は、和歌山県北東部に位置し、高野山への玄関口として知られる都市です。
  • A. Nagaokakyo City
    Nagaokakyo City is a suburban city in Kyoto Prefecture, Japan, known for its residential communities, historical temples, and convenient rail access to Kyoto and Osaka.
  • B. Morioka
    Morioka is the capital city of Iwate Prefecture in Japan’s Tōhoku region, known for its historic castle site, surrounding mountains, and distinctive local noodle dishes.
  • C. Maebashi
    Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
  • D. Kanazawa
    Kanazawa is a historic Japanese city on the Sea of Japan coast, renowned for its well-preserved samurai and geisha districts, traditional crafts, and the celebrated Kenrokuen Garden.
  • E. Bunkyō City
    Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
  • 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_69c0086b05cc8190a8f36a96927a525c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03983b8848190afaa37f35c95bad6 completed March 22, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3d1801c819093dc43dc5a525796 completed March 23, 2026, 6:55 a.m.
NEDg Description generation batch_69c0e781af588190a8f5572a03b24822 completed March 23, 2026, 7:10 a.m.
NED2 Entity disambiguation (via description) batch_69c0e7f767f8819086026b95c4534733 completed March 23, 2026, 7:12 a.m.
Created at: March 22, 2026, 4:02 p.m.