Triple

T12632137
Position Surface form Disambiguated ID Type / Status
Subject Takadanobaba E301669 entity
Predicate hasJapaneseName P9882 FINISHED
Object 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.
 E998160 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: 高田馬場 | Statement: [Takadanobaba, hasJapaneseName, 高田馬場]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 高田馬場
Context triple: [Takadanobaba, hasJapaneseName, 高田馬場]
  • A. 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。
  • B. 神宮前
    神宮前 is a district in Shibuya, Tokyo, known for its proximity to Meiji Shrine and the fashionable Harajuku and Omotesando areas.
  • C. 代々木
    代々木 is a district in Tokyo’s Shibuya ward known for Yoyogi Park, major railway hubs like Yoyogi Station, and its mix of residential, commercial, and educational facilities.
  • 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. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • 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: 高田馬場
Triple: [Takadanobaba, hasJapaneseName, 高田馬場]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 高田馬場
Target entity description: 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.
  • A. 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。
  • B. 神宮前
    神宮前 is a district in Shibuya, Tokyo, known for its proximity to Meiji Shrine and the fashionable Harajuku and Omotesando areas.
  • C. 代々木
    代々木 is a district in Tokyo’s Shibuya ward known for Yoyogi Park, major railway hubs like Yoyogi Station, and its mix of residential, commercial, and educational facilities.
  • 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. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9610e4f408190946f37325d69375c completed April 10, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6719886708190823f6f7e94e4d199 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f6740129688190b286ce7acb4848c7 completed May 2, 2026, 10 p.m.
NED2 Entity disambiguation (via description) batch_69f675249d248190933421df49d3a2ab completed May 2, 2026, 10:05 p.m.
Created at: April 9, 2026, 5:15 p.m.