Triple

T14249221
Position Surface form Disambiguated ID Type / Status
Subject 赤坂御用地 E353212 entity
Predicate 周辺地域 P17964 FINISHED
Object 赤坂
赤坂は、東京都港区に位置し、官公庁や高級ホテル、飲食店が集まるビジネス・商業エリアとして知られる街です。
E1090342 NE FINISHED

How this triple was built (5 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: 赤坂 | Statement: [赤坂御用地, 周辺地域, 赤坂]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 赤坂
Context triple: [赤坂御用地, 周辺地域, 赤坂]
  • A. 赤坂御用地
    赤坂御用地は、東京都港区赤坂に位置する日本の皇室関連施設が集まる広大な御用地で、皇族方の御所や宮邸が置かれているエリアである。
  • B. 大手町
    大手町 is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
  • C. 高田馬場
    高田馬場 is a bustling neighborhood in Tokyo’s Shinjuku ward known for its major train station, student population, and numerous eateries and entertainment spots.
  • D. 下北沢
    下北沢は東京都世田谷区に位置する、古着店やライブハウス、個性的なカフェが集まる若者文化とサブカルチャーの発信地として知られる街です。
  • E. 北沢
    北沢は、東京都世田谷区に位置する住宅地と商業地が混在した地域で、下北沢などの繁華なエリアを含む街区である。
  • 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: 赤坂
Triple: [赤坂御用地, 周辺地域, 赤坂]
Generated description
赤坂は、東京都港区に位置し、官公庁や高級ホテル、飲食店が集まるビジネス・商業エリアとして知られる街です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 赤坂
Target entity description: 赤坂は、東京都港区に位置し、官公庁や高級ホテル、飲食店が集まるビジネス・商業エリアとして知られる街です。
  • A. 赤坂御用地
    赤坂御用地は、東京都港区赤坂に位置する日本の皇室関連施設が集まる広大な御用地で、皇族方の御所や宮邸が置かれているエリアである。
  • B. 大手町
    大手町 is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
  • C. 高田馬場
    高田馬場 is a bustling neighborhood in Tokyo’s Shinjuku ward known for its major train station, student population, and numerous eateries and entertainment spots.
  • D. 下北沢
    下北沢は東京都世田谷区に位置する、古着店やライブハウス、個性的なカフェが集まる若者文化とサブカルチャーの発信地として知られる街です。
  • E. 北沢
    北沢は、東京都世田谷区に位置する住宅地と商業地が混在した地域で、下北沢などの繁華なエリアを含む街区である。
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: 周辺地域
Context triple: [赤坂御用地, 周辺地域, 赤坂]
  • A. nearbySettlementRegion
    Indicates that a settlement is located close to or within the surrounding area of a specified region.
  • B. regionOfCity
    Indicates that a specified area or district is a constituent part or subdivision of a particular city.
  • C. neighboringRegion chosen
    Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
  • D. nearbyRegionCharacterizedBy
    Indicates that a region located nearby another entity is defined or distinguished by a particular characteristic, feature, or condition.
  • E. hasNearbyPrefecture
    Indicates that one administrative region has another prefecture located geographically close to it.
  • F. None of above.

Provenance (6 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6295ef9081909cfb0c1283bca21a completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd325815d48190b070866f41986847 completed May 8, 2026, 12:46 a.m.
NEDg Description generation batch_69fd367fd9788190bd25f057d1f0942c completed May 8, 2026, 1:04 a.m.
NED2 Entity disambiguation (via description) batch_69fd37c1f4c0819085f5c577e673e9df completed May 8, 2026, 1:09 a.m.
PD Predicate disambiguation batch_69de05c09b7881908acbca18bd7d997c completed April 14, 2026, 9:15 a.m.
Created at: April 10, 2026, 1:08 a.m.