Triple

T5936596
Position Surface form Disambiguated ID Type / Status
Subject 吉田茂 E132059 entity
Predicate 死亡地 P21 FINISHED
Object 日本・東京都港区
日本・東京都港区は、東京湾に面し多くの大企業本社や大使館、商業施設が集まる東京都心の主要な行政区の一つです。
E557098 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: 日本・東京都港区 | Statement: [吉田茂, 死亡地, 日本・東京都港区]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 日本・東京都港区
Context triple: [吉田茂, 死亡地, 日本・東京都港区]
  • A. Itabashi, Tokyo
    Itabashi, Tokyo is one of Tokyo's 23 special wards, located in the northwestern part of the metropolis and known as a primarily residential and commercial area.
  • B. Toshima, Tokyo
    Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
  • C. Kōtō, Tokyo, Japan
    Kōtō is a special ward in eastern Tokyo known for its waterfront areas, reclaimed land, and a mix of residential neighborhoods, commercial districts, and large-scale facilities.
  • D. Ichigaya district, Tokyo
    Ichigaya district, Tokyo is a central Tokyo neighborhood known for hosting major government and defense institutions, including Japan’s Ministry of Defense.
  • E. Bunkyo, Tokyo
    Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
  • 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: 日本・東京都港区
Triple: [吉田茂, 死亡地, 日本・東京都港区]
Generated description
日本・東京都港区は、東京湾に面し多くの大企業本社や大使館、商業施設が集まる東京都心の主要な行政区の一つです。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 日本・東京都港区
Target entity description: 日本・東京都港区は、東京湾に面し多くの大企業本社や大使館、商業施設が集まる東京都心の主要な行政区の一つです。
  • A. Itabashi, Tokyo
    Itabashi, Tokyo is one of Tokyo's 23 special wards, located in the northwestern part of the metropolis and known as a primarily residential and commercial area.
  • B. Toshima, Tokyo
    Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
  • C. Kōtō, Tokyo, Japan
    Kōtō is a special ward in eastern Tokyo known for its waterfront areas, reclaimed land, and a mix of residential neighborhoods, commercial districts, and large-scale facilities.
  • D. Ichigaya district, Tokyo
    Ichigaya district, Tokyo is a central Tokyo neighborhood known for hosting major government and defense institutions, including Japan’s Ministry of Defense.
  • E. Bunkyo, Tokyo
    Bunkyo, Tokyo is a central special ward of Tokyo known for its educational institutions, cultural sites, and major sports venues such as the Tokyo Dome.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c038eca9688190adeed21df058daf1 completed March 22, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c06f979881908d7e98ee674f1ff2 completed March 23, 2026, 4:24 a.m.
NEDg Description generation batch_69c0c329b1108190ac4fe897e2be9946 completed March 23, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c0c3a81a608190a39283b4df0ab4b9 completed March 23, 2026, 4:38 a.m.
Created at: March 22, 2026, 4:01 p.m.