Triple

T20282152
Position Surface form Disambiguated ID Type / Status
Subject Hayashi E503174 entity
Predicate orthographicVariant P33995 FINISHED
Object ハヤシ 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: ハヤシ | Statement: [Hayashi, orthographicVariant, ハヤシ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ハヤシ
Context triple: [Hayashi, orthographicVariant, ハヤシ]
  • A. Hayashi chosen
    Hayashi is a common Japanese surname that literally means "forest" and is equivalent to the Chinese surname "Lin."
  • B. Katsu Awa
    Katsu Awa, better known as Katsu Kaishū, was a prominent late-Edo and early Meiji Japanese naval officer and statesman who played a key role in modernizing Japan’s navy and negotiating the peaceful surrender of Edo.
  • C. Shiso
    Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
  • D. Rao Shushi
    Rao Shushi was a senior Chinese Communist Party leader and revolutionary who held key political and military posts in the early People’s Republic of China before later being purged.
  • E. Shōkū
    Shōkū was a prominent Japanese Buddhist monk of the Kamakura period and a leading disciple of Hōnen who helped develop and spread Pure Land (Jōdo) teachings.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6768f86448190842389a98b93a918 completed April 20, 2026, 6:55 p.m.
Created at: April 16, 2026, 10:39 a.m.