Triple

T17023605
Position Surface form Disambiguated ID Type / Status
Subject Tomoko Satō E413007 entity
Predicate givenName P17 FINISHED
Object Tomoko
Tomoko is a common Japanese feminine given name that can have various meanings depending on the kanji characters used to write it.
 E1295259 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: Tomoko | Statement: [Tomoko Satō, givenName, Tomoko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tomoko
Context triple: [Tomoko Satō, givenName, Tomoko]
  • A. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • B. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • C. Tomomi
    Tomomi is a Japanese given name that can be used for people of any gender.
  • D. Misako
    Misako is a key character in the Ninjago universe, known as an archaeologist and historian who is the mother of Lloyd Garmadon and the wife of Garmadon.
  • E. Junko
    Junko is a common Japanese feminine given name borne by numerous notable figures in fields such as entertainment, sports, and the arts.
  • 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: Tomoko
Triple: [Tomoko Satō, givenName, Tomoko]
Generated description
Tomoko is a common Japanese feminine given name that can have various meanings depending on the kanji characters used to write it.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tomoko
Target entity description: Tomoko is a common Japanese feminine given name that can have various meanings depending on the kanji characters used to write it.
  • A. Takako
    Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
  • B. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • C. Tomomi
    Tomomi is a Japanese given name that can be used for people of any gender.
  • D. Misako
    Misako is a key character in the Ninjago universe, known as an archaeologist and historian who is the mother of Lloyd Garmadon and the wife of Garmadon.
  • E. Junko
    Junko is a common Japanese feminine given name borne by numerous notable figures in fields such as entertainment, sports, and the arts.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d2abbc81908943becf5f539fc6 completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a031b10f34c81908bd52d2d581da69a completed May 12, 2026, 12:20 p.m.
NEDg Description generation batch_6a031db1ca588190aac180a4fd87383e completed May 12, 2026, 12:31 p.m.
NED2 Entity disambiguation (via description) batch_6a031e67a8bc81909f1076d175f5af2c completed May 12, 2026, 12:34 p.m.
Created at: April 10, 2026, 5:33 a.m.