Triple

T6236857
Position Surface form Disambiguated ID Type / Status
Subject central Tokyo E139497 entity
Predicate contains P35 FINISHED
Object Hamamatsuchō
Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
E602853 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: Hamamatsuchō | Statement: [central Tokyo, contains, Hamamatsuchō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamamatsuchō
Context triple: [central Tokyo, contains, Hamamatsuchō]
  • A. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • B. Nishi-Tobecho
    Nishi-Tobecho is a notable neighborhood within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
  • C. Musashi-Koyama
    Musashi-Koyama is a lively neighborhood in Tokyo known for its long covered shopping street, local eateries, and convenient urban living.
  • D. Bunkyō
    Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • E. Sawara-ku
    Sawara-ku is one of the wards of Fukuoka City in Japan, known for its mix of residential areas, universities, and coastal attractions along the Sea of Japan.
  • 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: Hamamatsuchō
Triple: [central Tokyo, contains, Hamamatsuchō]
Generated description
Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hamamatsuchō
Target entity description: Hamamatsuchō is a business and transportation district in Tokyo known for its major train and monorail stations, office towers, and proximity to Tokyo Bay.
  • A. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • B. Nishi-Tobecho
    Nishi-Tobecho is a notable neighborhood within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
  • C. Musashi-Koyama
    Musashi-Koyama is a lively neighborhood in Tokyo known for its long covered shopping street, local eateries, and convenient urban living.
  • D. Bunkyō
    Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • E. Sawara-ku
    Sawara-ku is one of the wards of Fukuoka City in Japan, known for its mix of residential areas, universities, and coastal attractions along the Sea of Japan.
  • 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_69c008b0e7ac8190808a59573ee646f3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063021258819093a9237041816638 completed March 22, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d4fdd7288190bb9aef680beb906d completed March 27, 2026, 7:05 p.m.
NEDg Description generation batch_69c6d622831c8190b09b8539e36afb7c completed March 27, 2026, 7:10 p.m.
NED2 Entity disambiguation (via description) batch_69c6d6b00ebc8190b893b3e209bf07c0 completed March 27, 2026, 7:12 p.m.
Created at: March 22, 2026, 4:23 p.m.