Triple

T2327407
Position Surface form Disambiguated ID Type / Status
Subject Nishinomiya E48319 entity
Predicate hasRiver P165 FINISHED
Object Mukogawa River E210314 NE FINISHED

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: Mukogawa River | Statement: [Nishinomiya, hasRiver, Mukogawa River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mukogawa River
Context triple: [Nishinomiya, hasRiver, Mukogawa River]
  • A. Mukogawa River chosen
    The Mukogawa River is a prominent river in Japan’s Hyōgo Prefecture that flows through cities such as Nishinomiya before emptying into Osaka Bay.
  • B. Shinano River
    The Shinano River is Japan’s longest river, flowing through central Honshu before emptying into the Sea of Japan.
  • C. Furan River
    The Furan River is a watercourse in eastern France that flows through the Loire department and the city of Saint-Étienne before joining the Ain River.
  • D. Yamato River
    The Yamato River is a major river in Japan’s Kansai region that flows through Nara and Osaka Prefectures before emptying into Osaka Bay.
  • E. Okano River
    The Okano River is a significant river in Gabon that serves as one of the principal tributaries feeding the Ogooué River system.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc64c7f1881909b0d847f7782e803 completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0559d1e708190bc8d28ed3706ae23 completed March 10, 2026, 5:32 p.m.
Created at: March 4, 2026, 7:50 p.m.