Triple

T21379516
Position Surface form Disambiguated ID Type / Status
Subject Mako Komuro E527305 entity
Predicate familyName P18 FINISHED
Object Komuro 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: Komuro | Statement: [Mako Komuro, familyName, Komuro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Komuro
Context triple: [Mako Komuro, familyName, Komuro]
  • A. Komuro chosen
    Komuro is the married surname of Japan’s former Princess Mako, adopted after her marriage to commoner Kei Komuro.
  • B. Koromo
    Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
  • C. Tsumago
    Tsumago is a well-preserved former post town on Japan’s historic Nakasendō route, known for its traditional wooden buildings and Edo-period atmosphere.
  • D. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • E. Mitoyo
    Mitoyo is a coastal city in western Kagawa Prefecture on Japan’s Shikoku Island, known for its scenic Seto Inland Sea views and rural landscapes.
  • 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_69e0b51f363c8190944000ab5523b02b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0cc2b5c8190aa5f20f920523fe9 completed April 22, 2026, 11:28 a.m.
Created at: April 16, 2026, 5:11 p.m.