Triple

T18351038
Position Surface form Disambiguated ID Type / Status
Subject Haruki Murakami E439666 entity
Predicate spouse P13 FINISHED
Object Yoko Murakami NE NERFINISHED

How this triple was built (2 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: Yoko Murakami | Statement: [Haruki Murakami, spouse, Yoko Murakami]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yoko Murakami
Context triple: [Haruki Murakami, spouse, Yoko Murakami]
  • A. Yoko Murakami chosen
    Yoko Murakami is the wife of acclaimed Japanese novelist Haruki Murakami and has been a close creative and personal partner throughout his literary career.
  • B. Reiko Murakami
    Reiko Murakami is an illustrator and cover artist known for her atmospheric, often darkly surreal artwork in contemporary fantasy and horror media.
  • C. Yoko Ogawa
    Yoko Ogawa is a Japanese author renowned for her quietly unsettling, psychologically rich fiction, including works like "The Housekeeper and the Professor" and "The Memory Police."
  • D. Kawakami Mieko
    Kawakami Mieko is a contemporary Japanese novelist and former musician known internationally for her feminist, socially incisive works such as "Breasts and Eggs."
  • E. Kawakami Yōko
    Kawakami Yōko is a Japanese writer known for her imaginative, genre-blending fiction and contributions to contemporary Japanese literature.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f83b648190b473cf611851c666 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 10:37 a.m.