Triple

T3877557
Position Surface form Disambiguated ID Type / Status
Subject Satō E92538 entity
Predicate hasNotableBearer P458 FINISHED
Object Rina Satō
Rina Satō is a Japanese voice actress known for her roles in numerous anime series, video games, and other media.
E416024 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: Rina Satō | Statement: [Satō, hasNotableBearer, Rina Satō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rina Satō
Context triple: [Satō, hasNotableBearer, Rina Satō]
  • A. Yuki Satō
    Yuki Satō is a Japanese name shared by multiple notable individuals, including athletes and entertainers, distinguished in their respective fields.
  • B. Yoshiko Satō
    Yoshiko Satō is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Satō.
  • C. Yui Satō
    Yui Satō is a Japanese given name borne by multiple notable individuals, including figures in entertainment and other public fields.
  • D. Miki Satō
    Miki Satō is a Japanese singer-songwriter known for her emotionally expressive vocals and contributions to anime theme songs.
  • E. Sanae Takaichi
    Sanae Takaichi is a Japanese conservative politician of the Liberal Democratic Party who has served in several ministerial posts and is known for her bids for party leadership and advocacy of hawkish security and traditionalist social policies.
  • 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: Rina Satō
Triple: [Satō, hasNotableBearer, Rina Satō]
Generated description
Rina Satō is a Japanese voice actress known for her roles in numerous anime series, video games, and other media.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rina Satō
Target entity description: Rina Satō is a Japanese voice actress known for her roles in numerous anime series, video games, and other media.
  • A. Yuki Satō
    Yuki Satō is a Japanese name shared by multiple notable individuals, including athletes and entertainers, distinguished in their respective fields.
  • B. Yoshiko Satō
    Yoshiko Satō is a Japanese individual notable enough to be recognized as a prominent bearer of the surname Satō.
  • C. Yui Satō
    Yui Satō is a Japanese given name borne by multiple notable individuals, including figures in entertainment and other public fields.
  • D. Miki Satō
    Miki Satō is a Japanese singer-songwriter known for her emotionally expressive vocals and contributions to anime theme songs.
  • E. Sanae Takaichi
    Sanae Takaichi is a Japanese conservative politician of the Liberal Democratic Party who has served in several ministerial posts and is known for her bids for party leadership and advocacy of hawkish security and traditionalist social policies.
  • 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec72fa7c81909c73b3cf90597e9a completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576852d0c819083d377bab6799ec7 completed March 14, 2026, 2:53 p.m.
NEDg Description generation batch_69b577ac31888190b6182b00bd5c709f completed March 14, 2026, 2:58 p.m.
NED2 Entity disambiguation (via description) batch_69b57839ee548190804ef306fc9b3a6e completed March 14, 2026, 3:01 p.m.
Created at: March 9, 2026, 3:20 p.m.