Triple

T2929219
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Wood (2010 film) E78918 entity
Predicate castMember P1668 FINISHED
Object Kengo Kora
Kengo Kora is a Japanese actor known for his roles in contemporary Japanese cinema and television dramas.
E312337 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: Kengo Kora | Statement: [Norwegian Wood (2010 film), castMember, Kengo Kora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kengo Kora
Context triple: [Norwegian Wood (2010 film), castMember, Kengo Kora]
  • A. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • B. Katsuya
    Katsuya is a Japanese given name commonly used for males.
  • C. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • D. Kōjun Kōgō
    Kōjun Kōgō was the Empress consort of Japan as the wife of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito.
  • E. Masahito
    Masahito is the personal name of Prince Hitachi, a member of the Japanese imperial family and younger brother of Emperor Emeritus Akihito.
  • 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: Kengo Kora
Triple: [Norwegian Wood (2010 film), castMember, Kengo Kora]
Generated description
Kengo Kora is a Japanese actor known for his roles in contemporary Japanese cinema and television dramas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kengo Kora
Target entity description: Kengo Kora is a Japanese actor known for his roles in contemporary Japanese cinema and television dramas.
  • A. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • B. Katsuya
    Katsuya is a Japanese given name commonly used for males.
  • C. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • D. Kōjun Kōgō
    Kōjun Kōgō was the Empress consort of Japan as the wife of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito.
  • E. Masahito
    Masahito is the personal name of Prince Hitachi, a member of the Japanese imperial family and younger brother of Emperor Emeritus Akihito.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98002da4819098d6448eebcafad4 completed March 8, 2026, 3:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0866c24c88190af6c5246b5c78c70 completed March 10, 2026, 9 p.m.
NEDg Description generation batch_69b0d55128fc8190919354199e4c21bf completed March 11, 2026, 2:37 a.m.
NED2 Entity disambiguation (via description) batch_69b0d5f35adc81909af0a7cafbeb92de completed March 11, 2026, 2:39 a.m.
Created at: March 8, 2026, 2:55 p.m.