Triple

T17436389
Position Surface form Disambiguated ID Type / Status
Subject Ran E424010 entity
Predicate costumeDesigner P184 FINISHED
Object Emi Wada
Emi Wada was an acclaimed Japanese costume designer renowned for her elaborate, historically inspired work in film, theater, and opera, including her Academy Award–winning designs for Akira Kurosawa’s epic "Ran."
 E1268725 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: Emi Wada | Statement: [Ran, costumeDesigner, Emi Wada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emi Wada
Context triple: [Ran, costumeDesigner, Emi Wada]
  • A. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • B. Iiyama
    Iiyama is a small city in Nagano Prefecture, Japan, known as a gateway to nearby ski resorts and for its snowy winters and rural mountain scenery.
  • C. Iiyama
    Iiyama is a Japanese electronics manufacturer best known for producing high-quality computer monitors and display solutions.
  • D. Emori
    Emori is a Japanese given name that can be used for individuals of any gender.
  • E. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • 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: Emi Wada
Triple: [Ran, costumeDesigner, Emi Wada]
Generated description
Emi Wada was an acclaimed Japanese costume designer renowned for her elaborate, historically inspired work in film, theater, and opera, including her Academy Award–winning designs for Akira Kurosawa’s epic "Ran."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emi Wada
Target entity description: Emi Wada was an acclaimed Japanese costume designer renowned for her elaborate, historically inspired work in film, theater, and opera, including her Academy Award–winning designs for Akira Kurosawa’s epic "Ran."
  • A. Kamiyama
    Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
  • B. Iiyama
    Iiyama is a small city in Nagano Prefecture, Japan, known as a gateway to nearby ski resorts and for its snowy winters and rural mountain scenery.
  • C. Iiyama
    Iiyama is a Japanese electronics manufacturer best known for producing high-quality computer monitors and display solutions.
  • D. Emori
    Emori is a Japanese given name that can be used for individuals of any gender.
  • E. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490426008190b474ed76aca5d6f3 completed April 19, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01aff0b26c8190a6e65451e52199bb completed May 11, 2026, 10:31 a.m.
NEDg Description generation batch_6a01b12b5df4819089fd89fd25338533 completed May 11, 2026, 10:36 a.m.
NED2 Entity disambiguation (via description) batch_6a01b17486c08190aa47953e74c62e84 completed May 11, 2026, 10:37 a.m.
Created at: April 10, 2026, 5:46 a.m.