Triple

T18584056
Position Surface form Disambiguated ID Type / Status
Subject 檜山修之 E454193 entity
Predicate voicedCharacter P2000 FINISHED
Object 相田ケンスケ
相田ケンスケは、アニメ『新世紀エヴァンゲリオン』に登場する、軍事オタク気質の中学生で碇シンジのクラスメイトとして知られるキャラクターである。
E1331908 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: 相田ケンスケ | Statement: [檜山修之, voicedCharacter, 相田ケンスケ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 相田ケンスケ
Context triple: [檜山修之, voicedCharacter, 相田ケンスケ]
  • A. Kenta Satō
    Kenta Satō is a Japanese individual notable enough to be recognized as a bearer of the surname Satō, though specific widely known achievements or roles are not clearly established.
  • B. Sakai Takashi
    Sakai Takashi was an Imperial Japanese Army general best known for leading Japanese forces during the early Pacific War, including the invasion of Hong Kong.
  • C. Tanaka Tatsuya
    Tanaka Tatsuya is a Japanese artist and photographer best known for his imaginative miniature dioramas that recreate everyday scenes using tiny figurines and household objects.
  • D. Yūsaku Kamekura
    Yūsaku Kamekura was a pioneering Japanese graphic designer renowned for his modernist posters and visual identities, including iconic work for the 1964 Tokyo Olympics.
  • E. Noda Kōichi
    Noda Kōichi is a Japanese architect best known for creating the iconic Kobe Port Tower, a landmark of Kobe’s waterfront skyline.
  • 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: 相田ケンスケ
Triple: [檜山修之, voicedCharacter, 相田ケンスケ]
Generated description
相田ケンスケは、アニメ『新世紀エヴァンゲリオン』に登場する、軍事オタク気質の中学生で碇シンジのクラスメイトとして知られるキャラクターである。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 相田ケンスケ
Target entity description: 相田ケンスケは、アニメ『新世紀エヴァンゲリオン』に登場する、軍事オタク気質の中学生で碇シンジのクラスメイトとして知られるキャラクターである。
  • A. Kenta Satō
    Kenta Satō is a Japanese individual notable enough to be recognized as a bearer of the surname Satō, though specific widely known achievements or roles are not clearly established.
  • B. Sakai Takashi
    Sakai Takashi was an Imperial Japanese Army general best known for leading Japanese forces during the early Pacific War, including the invasion of Hong Kong.
  • C. Tanaka Tatsuya
    Tanaka Tatsuya is a Japanese artist and photographer best known for his imaginative miniature dioramas that recreate everyday scenes using tiny figurines and household objects.
  • D. Yūsaku Kamekura
    Yūsaku Kamekura was a pioneering Japanese graphic designer renowned for his modernist posters and visual identities, including iconic work for the 1964 Tokyo Olympics.
  • E. Noda Kōichi
    Noda Kōichi is a Japanese architect best known for creating the iconic Kobe Port Tower, a landmark of Kobe’s waterfront skyline.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e543d200dc8190b8797d731f4e4865 completed April 19, 2026, 9:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a04f88f6870819085ebffc7c77e483f completed May 13, 2026, 10:17 p.m.
NEDg Description generation batch_6a04f9fc493881909ba9159748d4f3fb completed May 13, 2026, 10:23 p.m.
NED2 Entity disambiguation (via description) batch_6a04fad8daa88190961d643d30a52aa7 completed May 13, 2026, 10:27 p.m.
Created at: April 10, 2026, 11:44 a.m.