Triple

T5024947
Position Surface form Disambiguated ID Type / Status
Subject Princess Sachiko E112951 entity
Predicate givenName P17 FINISHED
Object Sachiko
Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
 E493357 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: Sachiko | Statement: [Princess Sachiko, givenName, Sachiko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sachiko
Context triple: [Princess Sachiko, givenName, Sachiko]
  • A. Shigeko
    Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
  • B. Kazuko
    Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
  • C. Masako
    Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
  • D. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • E. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • 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: Sachiko
Triple: [Princess Sachiko, givenName, Sachiko]
Generated description
Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sachiko
Target entity description: Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
  • A. Shigeko
    Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
  • B. Kazuko
    Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
  • C. Masako
    Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
  • D. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • E. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • 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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd736a0f8c819091d06275954329e9 completed March 20, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba5b5f84819086b7af26923f0987 completed March 21, 2026, 3:33 p.m.
NEDg Description generation batch_69bebb50aef48190b625278340a8c310 completed March 21, 2026, 3:37 p.m.
NED2 Entity disambiguation (via description) batch_69bebc0b38e88190830eb74292e00e93 completed March 21, 2026, 3:40 p.m.
Created at: March 20, 2026, 1:36 p.m.