Triple

T12839677
Position Surface form Disambiguated ID Type / Status
Subject Shuji E307015 entity
Predicate canBeWrittenAs P12679 FINISHED
Object 秀二
秀二 is a masculine Japanese given name, typically read as "Shūji" or "Hideji," formed from kanji that often convey meanings related to excellence or talent.
 E1003593 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: 秀二 | Statement: [Shuji, canBeWrittenAs, 秀二]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 秀二
Context triple: [Shuji, canBeWrittenAs, 秀二]
  • A. 秀喜
    秀喜 is a Japanese given name, often read as "Hideki," commonly used for males.
  • B. 秀紀
    秀紀 is a Japanese given name, typically masculine, written with kanji that can convey meanings related to excellence or distinction.
  • C. Yang Yuyu
    Yang Yuyu is an actor known for appearing as a cast member in film or television productions.
  • D. 二子玉川
    二子玉川 is a riverside commercial and residential district in Tokyo known for its large shopping complexes, stylish cafes, and family-friendly urban development along the Tama River.
  • E. Ling Xiaosu
    Ling Xiaosu is a Chinese actor known for his roles in television dramas and for his former marriage to actress Yao Chen.
  • 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: 秀二
Triple: [Shuji, canBeWrittenAs, 秀二]
Generated description
秀二 is a masculine Japanese given name, typically read as "Shūji" or "Hideji," formed from kanji that often convey meanings related to excellence or talent.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 秀二
Target entity description: 秀二 is a masculine Japanese given name, typically read as "Shūji" or "Hideji," formed from kanji that often convey meanings related to excellence or talent.
  • A. 秀喜
    秀喜 is a Japanese given name, often read as "Hideki," commonly used for males.
  • B. 秀紀
    秀紀 is a Japanese given name, typically masculine, written with kanji that can convey meanings related to excellence or distinction.
  • C. Yang Yuyu
    Yang Yuyu is an actor known for appearing as a cast member in film or television productions.
  • D. 二子玉川
    二子玉川 is a riverside commercial and residential district in Tokyo known for its large shopping complexes, stylish cafes, and family-friendly urban development along the Tama River.
  • E. Ling Xiaosu
    Ling Xiaosu is a Chinese actor known for his roles in television dramas and for his former marriage to actress Yao Chen.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff11b4481909fb2f92c46186853 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68edd30e881909062e8f91f614990 completed May 2, 2026, 11:55 p.m.
NEDg Description generation batch_69f68f8e29508190b9c5b5ed88631bf8 completed May 2, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_69f69006c0288190a49ba8714cd19959 completed May 3, 2026, midnight
Created at: April 9, 2026, 5:35 p.m.