Triple

T13646827
Position Surface form Disambiguated ID Type / Status
Subject Toshi Yoshida E326124 entity
Predicate givenName P17 FINISHED
Object Toshi
Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
E1053753 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: Toshi | Statement: [Toshi Yoshida, givenName, Toshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toshi
Context triple: [Toshi Yoshida, givenName, Toshi]
  • A. Takatoshi
    Takatoshi is a masculine Japanese given name that can be written with various kanji combinations and is borne by multiple notable individuals in Japan.
  • B. Shoki
    "Shoki" is a popular Nigerian street-hop song by Lil Kesh that helped propel him to mainstream fame and popularized a viral dance of the same name.
  • C. Yoske
    Yoske is a diminutive or affectionate nickname commonly used as a short form of the Hebrew given name Yosef.
  • D. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • E. Tomonori
    Tomonori is a Japanese masculine given name used by various notable individuals in fields such as sports and entertainment.
  • 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: Toshi
Triple: [Toshi Yoshida, givenName, Toshi]
Generated description
Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Toshi
Target entity description: Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
  • A. Takatoshi
    Takatoshi is a masculine Japanese given name that can be written with various kanji combinations and is borne by multiple notable individuals in Japan.
  • B. Shoki
    "Shoki" is a popular Nigerian street-hop song by Lil Kesh that helped propel him to mainstream fame and popularized a viral dance of the same name.
  • C. Yoske
    Yoske is a diminutive or affectionate nickname commonly used as a short form of the Hebrew given name Yosef.
  • D. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • E. Tomonori
    Tomonori is a Japanese masculine given name used by various notable individuals in fields such as sports and entertainment.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc6073e888190965456a639839749 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78af948408190bca7f2e46863391e completed May 3, 2026, 5:50 p.m.
NEDg Description generation batch_69f78bd52b748190ab483ec7634a6549 completed May 3, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_69f78d277c5c8190970cb3cd0fd32905 completed May 3, 2026, 6 p.m.
Created at: April 9, 2026, 9:52 p.m.