Triple

T4214745
Position Surface form Disambiguated ID Type / Status
Subject Tsukuba E94187 entity
Predicate near P350 FINISHED
Object Mount Tsukuba E300701 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 Tsukuba | Statement: [Tsukuba, near, Mount Tsukuba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Tsukuba
Context triple: [Tsukuba, near, Mount Tsukuba]
  • A. Mount Tsukuba chosen
    Mount Tsukuba is a famous double-peaked mountain in Japan known for its scenic views, religious significance, and popular hiking trails.
  • B. Mount Katsuragi
    Mount Katsuragi is a mountain on the border of Nara and Osaka Prefectures in Japan, known for its scenic hiking trails and seasonal flower displays, especially azaleas.
  • C. Mount Ōminakami
    Mount Ōminakami is a mountain in Japan known primarily as the headwaters area of the Tone River, one of the country’s major river systems.
  • D. Mount Suiro
    Mount Suiro is the tallest mountain on Biliran Island in the Philippines, forming a prominent part of the island’s volcanic landscape.
  • E. Mount Hachiman
    Mount Hachiman is a scenic hill in Ōmihachiman, Shiga Prefecture, known for its historical significance, hiking trails, and panoramic views over the city and Lake Biwa.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34be8ba408190baee362e5abbe75b completed March 12, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d05b964881908d7d52b70cec2dcc completed March 14, 2026, 9:17 p.m.
Created at: March 12, 2026, 11:04 p.m.