Triple

T1366314
Position Surface form Disambiguated ID Type / Status
Subject Sendagaya E30009 entity
Predicate hasJapaneseName P9882 FINISHED
Object 千駄ヶ谷
千駄ヶ谷は、東京都渋谷区に位置し、新国立競技場や明治神宮外苑などが近接する住宅地兼文教・スポーツエリアです。
 E286864 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: 千駄ヶ谷 | Statement: [Sendagaya, hasJapaneseName, 千駄ヶ谷]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 千駄ヶ谷
Context triple: [Sendagaya, hasJapaneseName, 千駄ヶ谷]
  • A. Setagaya
    Setagaya is a large residential ward in western Tokyo, Japan, known for its suburban neighborhoods, parks, and role as a commuter area for central Tokyo.
  • B. Shinagawa
    Shinagawa is a major commercial and transportation hub in Tokyo, Japan, known for its busy railway station, business districts, and waterfront developments.
  • C. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • D. Ikebukuro
    Ikebukuro is a major commercial and entertainment district in Tokyo known for its large train station, shopping complexes, and vibrant youth culture.
  • E. Shibuya
    Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
  • 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: 千駄ヶ谷
Triple: [Sendagaya, hasJapaneseName, 千駄ヶ谷]
Generated description
千駄ヶ谷は、東京都渋谷区に位置し、新国立競技場や明治神宮外苑などが近接する住宅地兼文教・スポーツエリアです。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 千駄ヶ谷
Target entity description: 千駄ヶ谷は、東京都渋谷区に位置し、新国立競技場や明治神宮外苑などが近接する住宅地兼文教・スポーツエリアです。
  • A. Setagaya
    Setagaya is a large residential ward in western Tokyo, Japan, known for its suburban neighborhoods, parks, and role as a commuter area for central Tokyo.
  • B. Shinagawa
    Shinagawa is a major commercial and transportation hub in Tokyo, Japan, known for its busy railway station, business districts, and waterfront developments.
  • C. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • D. Ikebukuro
    Ikebukuro is a major commercial and entertainment district in Tokyo known for its large train station, shopping complexes, and vibrant youth culture.
  • E. Shibuya
    Shibuya is a major commercial and entertainment district in Tokyo, Japan, famous for its bustling streets, youth culture, and iconic landmarks.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d1d15481909d58b6fd8aa2e585 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69af9893d2048190ac3b36c32f14b63d completed March 10, 2026, 4:05 a.m.
NEDg Description generation batch_69af9990f77081908a03b454fad1fad9 completed March 10, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69af99fe48f881908a1a20f5eed8688c completed March 10, 2026, 4:11 a.m.
Created at: March 1, 2026, 7:57 p.m.