Triple

T8437578
Position Surface form Disambiguated ID Type / Status
Subject Akinobu Mayumi E199266 entity
Predicate familyName P18 FINISHED
Object Mayumi
Mayumi is a Japanese surname borne by various individuals, including Akinobu Mayumi, and can also be used as a given name.
 E735444 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: Mayumi | Statement: [Akinobu Mayumi, familyName, Mayumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mayumi
Context triple: [Akinobu Mayumi, familyName, Mayumi]
  • A. Mayumi Kai
    Mayumi Kai is a Japanese DJ and music producer best known as the widow of The Prodigy frontman Keith Flint.
  • B. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • C. Yuzuriha
    Yuzuriha is an evergreen tree commonly used in Japan as a symbolic plant, notably serving as the official tree emblem of Kōchi Prefecture.
  • D. Naoko
    Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
  • E. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • 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: Mayumi
Triple: [Akinobu Mayumi, familyName, Mayumi]
Generated description
Mayumi is a Japanese surname borne by various individuals, including Akinobu Mayumi, and can also be used as a given name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mayumi
Target entity description: Mayumi is a Japanese surname borne by various individuals, including Akinobu Mayumi, and can also be used as a given name.
  • A. Mayumi Kai
    Mayumi Kai is a Japanese DJ and music producer best known as the widow of The Prodigy frontman Keith Flint.
  • B. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • C. Yuzuriha
    Yuzuriha is an evergreen tree commonly used in Japan as a symbolic plant, notably serving as the official tree emblem of Kōchi Prefecture.
  • D. Naoko
    Naoko is a central, emotionally fragile character in Haruki Murakami’s story "Norwegian Wood," whose complex relationship with the protagonist explores themes of love, loss, and mental illness.
  • E. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe13446788190ad52a4fd6e8b498a completed March 31, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce399e8efc8190ad6fa8a6cf91797c completed April 2, 2026, 9:40 a.m.
NEDg Description generation batch_69ce3b31397c81908c9ae4d19095b66d completed April 2, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69ce3bbf0eb481908e48c8b2eada1f16 completed April 2, 2026, 9:49 a.m.
Created at: March 30, 2026, 6:08 p.m.