Triple

T8308036
Position Surface form Disambiguated ID Type / Status
Subject Princess Nobuko E194513 entity
Predicate givenName P17 FINISHED
Object Nobuko
Nobuko is a Japanese feminine given name commonly borne by women of noble or imperial background.
E763850 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: Nobuko | Statement: [Princess Nobuko, givenName, Nobuko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nobuko
Context triple: [Princess Nobuko, givenName, Nobuko]
  • A. Sachiko
    Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
  • 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. Yoshiko
    Yoshiko is a feminine Japanese given name commonly used across various generations and often associated with traditional Japanese culture.
  • E. Shigeko
    Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
  • 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: Nobuko
Triple: [Princess Nobuko, givenName, Nobuko]
Generated description
Nobuko is a Japanese feminine given name commonly borne by women of noble or imperial background.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nobuko
Target entity description: Nobuko is a Japanese feminine given name commonly borne by women of noble or imperial background.
  • A. Sachiko
    Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
  • 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. Yoshiko
    Yoshiko is a feminine Japanese given name commonly used across various generations and often associated with traditional Japanese culture.
  • E. Shigeko
    Shigeko is a Japanese feminine given name that has been borne by various notable women, including members of the imperial family.
  • 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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f2c06608190bd21633af07a530b completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab01c58c81909148dacad2dc7667 completed April 3, 2026, 11:56 a.m.
NEDg Description generation batch_69cfac76d0f8819090c2bff520db52f4 completed April 3, 2026, 12:03 p.m.
NED2 Entity disambiguation (via description) batch_69cfad04e514819084bf30b8f026c031 completed April 3, 2026, 12:05 p.m.
Created at: March 30, 2026, 5:54 p.m.