Triple

T6735467
Position Surface form Disambiguated ID Type / Status
Subject Tanaka E153742 entity
Predicate hasNotablePerson P304 FINISHED
Object Tanaka Makiko
Tanaka Makiko is a Japanese politician and former foreign minister known for her reformist stance and outspoken criticism of Japan’s political establishment.
E658949 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: Tanaka Makiko | Statement: [Tanaka, hasNotablePerson, Tanaka Makiko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanaka Makiko
Context triple: [Tanaka, hasNotablePerson, Tanaka Makiko]
  • A. Naoko Takeshita
    Naoko Takeshita was the wife of former Japanese Prime Minister Noboru Takeshita and a member of a prominent political family in Japan.
  • B. Akiko Takeshita
    Akiko Takeshita is a Japanese actress known internationally for her supporting role in the film "Lost in Translation."
  • C. Ikeda Tomoko
    Ikeda Tomoko is a Japanese individual notable enough to be specifically cited as a bearer of the surname Ikeda.
  • D. Chikako Shimazu
    Chikako Shimazu was a Japanese noblewoman of the influential Shimazu family and the mother of Empress Kōjun, consort of Emperor Shōwa (Hirohito).
  • E. Naoko Satō
    Naoko Satō is a Japanese given name borne by various notable individuals, including figures in 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: Tanaka Makiko
Triple: [Tanaka, hasNotablePerson, Tanaka Makiko]
Generated description
Tanaka Makiko is a Japanese politician and former foreign minister known for her reformist stance and outspoken criticism of Japan’s political establishment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tanaka Makiko
Target entity description: Tanaka Makiko is a Japanese politician and former foreign minister known for her reformist stance and outspoken criticism of Japan’s political establishment.
  • A. Naoko Takeshita
    Naoko Takeshita was the wife of former Japanese Prime Minister Noboru Takeshita and a member of a prominent political family in Japan.
  • B. Akiko Takeshita
    Akiko Takeshita is a Japanese actress known internationally for her supporting role in the film "Lost in Translation."
  • C. Ikeda Tomoko
    Ikeda Tomoko is a Japanese individual notable enough to be specifically cited as a bearer of the surname Ikeda.
  • D. Chikako Shimazu
    Chikako Shimazu was a Japanese noblewoman of the influential Shimazu family and the mother of Empress Kōjun, consort of Emperor Shōwa (Hirohito).
  • E. Naoko Satō
    Naoko Satō is a Japanese given name borne by various notable individuals, including figures in 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_69c6880bdd68819097de8b6099992682 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d16ecbe08190b019d547f631a725 completed March 27, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa57aa9c819081d4ec62bf18d971 completed March 28, 2026, 3:57 p.m.
NEDg Description generation batch_69c7fbafa2a08190bcfc407d1a6c0d2b completed March 28, 2026, 4:02 p.m.
NED2 Entity disambiguation (via description) batch_69c7fc14691481909d8d029c5c42cd14 completed March 28, 2026, 4:04 p.m.
Created at: March 27, 2026, 2:09 p.m.