Triple

T7606669
Position Surface form Disambiguated ID Type / Status
Subject Seiji E180122 entity
Predicate canBeWrittenAs P12679 FINISHED
Object 清司
清司 is a Japanese given name, typically read as "Seiji," used for males.
 E676793 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: 清司 | Statement: [Seiji, canBeWrittenAs, 清司]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 清司
Context triple: [Seiji, canBeWrittenAs, 清司]
  • A. Zongren
    Zongren is the given name of Li Zongren, a prominent Chinese military commander and political leader of the early to mid-20th century.
  • B. 詹
    詹 is a Chinese surname and character commonly romanized as "Chan" in Cantonese.
  • C. Hongzhi Zhengjue
    Hongzhi Zhengjue was a prominent 12th-century Chinese Chan master of the Caodong school, best known for developing and teaching the practice of silent illumination meditation.
  • D. 苏
    苏 is the standard Chinese abbreviation used to refer to Jiangsu Province in eastern China.
  • E. Shen Weijing
    Shen Weijing was a Ming dynasty military official and diplomat known for his controversial role in negotiating and commanding Chinese forces during the Japanese invasions of Korea in the late 16th century.
  • 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: 清司
Triple: [Seiji, canBeWrittenAs, 清司]
Generated description
清司 is a Japanese given name, typically read as "Seiji," used for males.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 清司
Target entity description: 清司 is a Japanese given name, typically read as "Seiji," used for males.
  • A. Zongren
    Zongren is the given name of Li Zongren, a prominent Chinese military commander and political leader of the early to mid-20th century.
  • B. 詹
    詹 is a Chinese surname and character commonly romanized as "Chan" in Cantonese.
  • C. Hongzhi Zhengjue
    Hongzhi Zhengjue was a prominent 12th-century Chinese Chan master of the Caodong school, best known for developing and teaching the practice of silent illumination meditation.
  • D. 苏
    苏 is the standard Chinese abbreviation used to refer to Jiangsu Province in eastern China.
  • E. Shen Weijing
    Shen Weijing was a Ming dynasty military official and diplomat known for his controversial role in negotiating and commanding Chinese forces during the Japanese invasions of Korea in the late 16th century.
  • 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9fe10408190b1c12bb8f911cea8 completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86857db14819086d5ebd825d30e77 completed March 28, 2026, 11:46 p.m.
NEDg Description generation batch_69c86a12e1f08190ab214f4e95e986db completed March 28, 2026, 11:53 p.m.
NED2 Entity disambiguation (via description) batch_69c86a5b6f188190aafbf2e9fcb8b972 completed March 28, 2026, 11:55 p.m.
Created at: March 27, 2026, 3:54 p.m.