Triple

T4300342
Position Surface form Disambiguated ID Type / Status
Subject Hideki E99818 entity
Predicate hasKanjiVariant P17917 FINISHED
Object 秀紀
秀紀 is a Japanese given name, typically masculine, written with kanji that can convey meanings related to excellence or distinction.
 E428569 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: 秀紀 | Statement: [Hideki, hasKanjiVariant, 秀紀]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 秀紀
Context triple: [Hideki, hasKanjiVariant, 秀紀]
  • A. Rina Satō
    Rina Satō is a Japanese voice actress known for her roles in numerous anime series, video games, and other media.
  • B. Ohira Chikako
    Ohira Chikako was the wife of Masayoshi Ōhira, the 68th Prime Minister of Japan, and served as a Japanese political spouse active in social and public life.
  • C. Koyama Mihoko
    Koyama Mihoko is a Japanese philanthropist and art collector best known as the founder and patron of the Miho Museum in Shiga Prefecture, Japan.
  • D. Yui Satō
    Yui Satō is a Japanese given name borne by multiple notable individuals, including figures in entertainment and other public fields.
  • E. 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.
  • 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: 秀紀
Triple: [Hideki, hasKanjiVariant, 秀紀]
Generated description
秀紀 is a Japanese given name, typically masculine, written with kanji that can convey meanings related to excellence or distinction.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 秀紀
Target entity description: 秀紀 is a Japanese given name, typically masculine, written with kanji that can convey meanings related to excellence or distinction.
  • A. Rina Satō
    Rina Satō is a Japanese voice actress known for her roles in numerous anime series, video games, and other media.
  • B. Ohira Chikako
    Ohira Chikako was the wife of Masayoshi Ōhira, the 68th Prime Minister of Japan, and served as a Japanese political spouse active in social and public life.
  • C. Koyama Mihoko
    Koyama Mihoko is a Japanese philanthropist and art collector best known as the founder and patron of the Miho Museum in Shiga Prefecture, Japan.
  • D. Yui Satō
    Yui Satō is a Japanese given name borne by multiple notable individuals, including figures in entertainment and other public fields.
  • E. 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.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509e8cb481909ccca7992aac31a3 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c74a1a7c8190a69a82a8a2a38db9 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7d04508819087b14c5c86f1e015 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c84ccea08190a8e7e8fa93934ea2 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:08 p.m.