Triple

T14167056
Position Surface form Disambiguated ID Type / Status
Subject 千代田区 E351107 entity
Predicate contains P35 FINISHED
Object 有楽町
有楽町は、東京都千代田区に位置し、オフィス街や商業施設、劇場などが集まる繁華な都心エリアです。
E1092824 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: 有楽町 | Statement: [千代田区, contains, 有楽町]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 有楽町
Context triple: [千代田区, contains, 有楽町]
  • A. Shinbashi
    Shinbashi is a historic commercial and entertainment district in central Tokyo known as a major business hub and gateway between the Ginza area and the Shiodome skyscraper complex.
  • B. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • C. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • D. Funabashi
    Funabashi is a major city in Chiba Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
  • E. 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.
  • 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: 有楽町
Triple: [千代田区, contains, 有楽町]
Generated description
有楽町は、東京都千代田区に位置し、オフィス街や商業施設、劇場などが集まる繁華な都心エリアです。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 有楽町
Target entity description: 有楽町は、東京都千代田区に位置し、オフィス街や商業施設、劇場などが集まる繁華な都心エリアです。
  • A. Shinbashi
    Shinbashi is a historic commercial and entertainment district in central Tokyo known as a major business hub and gateway between the Ginza area and the Shiodome skyscraper complex.
  • B. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • C. Kamitabashi
    Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
  • D. Funabashi
    Funabashi is a major city in Chiba Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
  • E. 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.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b355f08190864c7322bbcb766d completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4674da8881909dc6c1c8a36cf78e completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd477d0dd4819084116b385077324c completed May 8, 2026, 2:16 a.m.
NED2 Entity disambiguation (via description) batch_69fd4828f44c81908903d1391c83cc60 completed May 8, 2026, 2:19 a.m.
Created at: April 10, 2026, 1 a.m.