Triple

T6679329
Position Surface form Disambiguated ID Type / Status
Subject Ikeda E151936 entity
Predicate hasNotableBearer P458 FINISHED
Object Ikeda Riyoko
Ikeda Riyoko is a renowned Japanese manga artist best known for creating the influential historical shōjo series "The Rose of Versailles."
E649107 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: Ikeda Riyoko | Statement: [Ikeda, hasNotableBearer, Ikeda Riyoko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ikeda Riyoko
Context triple: [Ikeda, hasNotableBearer, Ikeda Riyoko]
  • A. Ikeda Yuki
    Ikeda Yuki is a Japanese individual notable for bearing the surname Ikeda, likely recognized in a specific professional or cultural field.
  • B. Nijō Motoko
    Nijō Motoko was a Japanese noblewoman of the Nijō family and the mother of Empress Teimei, consort of Emperor Taishō.
  • C. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • D. Koizumi Kyoko
    Koizumi Kyoko is a prominent Japanese singer and actress who rose to fame in the 1980s as an idol and later became acclaimed for her versatile film and television roles.
  • E. Kawashima Kiko
    Kawashima Kiko, better known as Princess Kiko, is a member of the Japanese imperial family and the wife of Crown Prince Fumihito (Prince Akishino).
  • 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: Ikeda Riyoko
Triple: [Ikeda, hasNotableBearer, Ikeda Riyoko]
Generated description
Ikeda Riyoko is a renowned Japanese manga artist best known for creating the influential historical shōjo series "The Rose of Versailles."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ikeda Riyoko
Target entity description: Ikeda Riyoko is a renowned Japanese manga artist best known for creating the influential historical shōjo series "The Rose of Versailles."
  • A. Ikeda Yuki
    Ikeda Yuki is a Japanese individual notable for bearing the surname Ikeda, likely recognized in a specific professional or cultural field.
  • B. Nijō Motoko
    Nijō Motoko was a Japanese noblewoman of the Nijō family and the mother of Empress Teimei, consort of Emperor Taishō.
  • C. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • D. Koizumi Kyoko
    Koizumi Kyoko is a prominent Japanese singer and actress who rose to fame in the 1980s as an idol and later became acclaimed for her versatile film and television roles.
  • E. Kawashima Kiko
    Kawashima Kiko, better known as Princess Kiko, is a member of the Japanese imperial family and the wife of Crown Prince Fumihito (Prince Akishino).
  • 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_69c687f830bc81909eb8b04dbb8450b1 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0f6813c8190906f619b4276a232 completed March 27, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf6c62948190a8e8f0d8f259ba42 completed March 28, 2026, 11:45 a.m.
NEDg Description generation batch_69c7c0cb1bc0819096daae8ab2202f0b completed March 28, 2026, 11:51 a.m.
NED2 Entity disambiguation (via description) batch_69c7c1352f8881909c3a7d03a5f2a5b1 completed March 28, 2026, 11:53 a.m.
Created at: March 27, 2026, 2:03 p.m.