Triple

T12594650
Position Surface form Disambiguated ID Type / Status
Subject Nikkō National Park E300702 entity
Predicate contains P35 FINISHED
Object Mount Nantai E304336 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: Mount Nantai | Statement: [Nikkō National Park, contains, Mount Nantai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Nantai
Context triple: [Nikkō National Park, contains, Mount Nantai]
  • A. Mount Nantai chosen
    Mount Nantai is a prominent stratovolcano in Japan known as a sacred mountain of Shinto and a scenic landmark near Lake Chūzenji in Nikkō.
  • B. Mount Tsurumi
    Mount Tsurumi is a volcanic mountain in Ōita Prefecture, Japan, known for its panoramic views, seasonal foliage, and ropeway access from the hot spring resort city of Beppu.
  • C. Mount Suiro
    Mount Suiro is the tallest mountain on Biliran Island in the Philippines, forming a prominent part of the island’s volcanic landscape.
  • D. Mount Goryu
    Mount Goryu is a prominent peak in Japan’s Northern Alps, known for its ski resorts and alpine hiking within the Hakuba Valley area.
  • E. Mount Sankaku
    Mount Sankaku is a small, popular hiking and viewpoint mountain located in Nishi-ku, Sapporo, Japan.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954cde3c0819094e74413d6dcf548 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af45ea888190a4b2d0c1730a06ef completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:08 p.m.