Triple

T10705822
Position Surface form Disambiguated ID Type / Status
Subject Shigeru Ban E252400 entity
Predicate nativeName P15 FINISHED
Object 坂 茂
坂 茂 is a renowned Japanese architect celebrated for his innovative use of paper and recyclable materials in humanitarian and disaster-relief structures.
E880364 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: 坂 茂 | Statement: [Shigeru Ban, nativeName, 坂 茂]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 坂 茂
Context triple: [Shigeru Ban, nativeName, 坂 茂]
  • A. 宮本 茂
    宮本 茂 is a legendary Japanese video game designer and producer at Nintendo, best known as the creator of iconic franchises such as Super Mario, The Legend of Zelda, and Donkey Kong.
  • B. 山口那津男
    山口那津男 is a Japanese politician who serves as the longtime leader of the Komeito party and has played a key role in Japan’s ruling coalition governments.
  • C. 杉本博司
    杉本博司は、長時間露光による海景や劇場シリーズなどで知られる、日本出身の世界的に著名な現代美術写真家・美術家です。
  • D. 久米邦武
    久米邦武 was a Meiji-era Japanese historian and scholar best known for documenting the Iwakura Mission and advancing modern historical studies in Japan.
  • E. 大山巌
    大山巌は、日清戦争・日露戦争で活躍し元帥陸軍大将となった、日本近代陸軍を代表する軍人・政治家である。
  • 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: 坂 茂
Triple: [Shigeru Ban, nativeName, 坂 茂]
Generated description
坂 茂 is a renowned Japanese architect celebrated for his innovative use of paper and recyclable materials in humanitarian and disaster-relief structures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 坂 茂
Target entity description: 坂 茂 is a renowned Japanese architect celebrated for his innovative use of paper and recyclable materials in humanitarian and disaster-relief structures.
  • A. 宮本 茂
    宮本 茂 is a legendary Japanese video game designer and producer at Nintendo, best known as the creator of iconic franchises such as Super Mario, The Legend of Zelda, and Donkey Kong.
  • B. 山口那津男
    山口那津男 is a Japanese politician who serves as the longtime leader of the Komeito party and has played a key role in Japan’s ruling coalition governments.
  • C. 杉本博司
    杉本博司は、長時間露光による海景や劇場シリーズなどで知られる、日本出身の世界的に著名な現代美術写真家・美術家です。
  • D. 久米邦武
    久米邦武 was a Meiji-era Japanese historian and scholar best known for documenting the Iwakura Mission and advancing modern historical studies in Japan.
  • E. 大山巌
    大山巌は、日清戦争・日露戦争で活躍し元帥陸軍大将となった、日本近代陸軍を代表する軍人・政治家である。
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fddeb060819094cd125a68070eb2 completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998fe56dc8190ae0c987b28ec6206 completed April 11, 2026, 12:42 a.m.
NEDg Description generation batch_69d99e8632688190b3746649a124ca09 completed April 11, 2026, 1:06 a.m.
NED2 Entity disambiguation (via description) batch_69da625a1e8c8190b282e7a70bb7c876 completed April 11, 2026, 3:01 p.m.
Created at: April 8, 2026, 9:12 p.m.