Triple

T12296374
Position Surface form Disambiguated ID Type / Status
Subject Mount Daimonji E293095 entity
Predicate viewOf P854 FINISHED
Object Kamo River E56456 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: Kamo River | Statement: [Mount Daimonji, viewOf, Kamo River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamo River
Context triple: [Mount Daimonji, viewOf, Kamo River]
  • A. Kamo River chosen
    The Kamo River is a prominent river running through Kyoto, Japan, known for its scenic banks, seasonal cherry blossoms, and role as a central gathering place for locals and visitors.
  • B. Kamogawa River
    The Kamogawa River is a prominent river flowing through Kyoto, Japan, known for its scenic banks lined with traditional teahouses, restaurants, and popular walking paths.
  • C. Yoshino River
    The Yoshino River is one of Japan’s major rivers, renowned for its strong currents, hydroelectric dams, and scenic gorges as it flows across the island of Shikoku.
  • D. Ōhashi River
    Ōhashi River is a short but significant river in Matsue, Shimane Prefecture, Japan, connecting Lake Shinji to Nakaumi and shaping the city's scenic waterfront.
  • E. Arakawa River
    The Arakawa River is a major river in the Tokyo region of Japan, known for its extensive flood control systems and role in shaping the urban landscape.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93ed903808190b7ed90e0db3d7586 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec869957481909ea4fded01851b70 completed May 9, 2026, 5:38 a.m.
Created at: April 8, 2026, 9:52 p.m.