Triple

T2450493
Position Surface form Disambiguated ID Type / Status
Subject Yamashita Tomoyuki E53691 entity
Predicate givenName P17 FINISHED
Object Tomoyuki
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
 E315805 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: Tomoyuki | Statement: [Yamashita Tomoyuki, givenName, Tomoyuki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tomoyuki
Context triple: [Yamashita Tomoyuki, givenName, Tomoyuki]
  • A. Shintaro
    Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
  • B. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • C. Tadahiko
    Tadahiko is a Japanese masculine given name used by various notable individuals in fields such as sports, arts, and academia.
  • D. Takashi
    Takashi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as arts, sports, and entertainment.
  • E. Akinobu
    Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
  • 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: Tomoyuki
Triple: [Yamashita Tomoyuki, givenName, Tomoyuki]
Generated description
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tomoyuki
Target entity description: Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
  • A. Shintaro
    Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
  • B. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • C. Tadahiko
    Tadahiko is a Japanese masculine given name used by various notable individuals in fields such as sports, arts, and academia.
  • D. Takashi
    Takashi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as arts, sports, and entertainment.
  • E. Akinobu
    Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0f402b48190b871b2475983af7e completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108bf1214819091291de2c8343764 completed March 11, 2026, 6:16 a.m.
NEDg Description generation batch_69b109e575588190a178d881a52d06e0 completed March 11, 2026, 6:21 a.m.
NED2 Entity disambiguation (via description) batch_69b10a8644208190bf0cf4d6d6d50bf0 completed March 11, 2026, 6:24 a.m.
Created at: March 6, 2026, 9:43 p.m.