Triple

T574372
Position Surface form Disambiguated ID Type / Status
Subject Shikoku E13729 entity
Predicate separatedFrom P243 FINISHED
Object Honshu E8910 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: Honshu | Statement: [Shikoku, separatedFrom, Honshu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Honshu
Context triple: [Shikoku, separatedFrom, Honshu]
  • A. Honshu chosen
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • B. Kyushu
    Kyushu is the southwesternmost of Japan’s main islands, known for its active volcanoes, hot springs, and historic cities such as Fukuoka and Nagasaki.
  • C. Hokkaido
    Hokkaido is Japan’s northernmost main island, known for its cold climate, vast natural landscapes, and popular ski resorts.
  • D. Japanese archipelago
    The Japanese archipelago is a chain of islands in East Asia that forms the country of Japan, stretching from Hokkaido in the north to Okinawa in the south.
  • E. Shikoku
    Shikoku is the smallest of Japan’s four main islands, known for its mountainous landscapes, traditional rural culture, and the famous 88-temple Buddhist pilgrimage route.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b4c23548190a3b883239c7c78c8 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56930dfd88190a991adafc406c5ac completed March 2, 2026, 10:40 a.m.
Created at: March 1, 2026, 7:33 p.m.