Triple

T949210
Position Surface form Disambiguated ID Type / Status
Subject Aleutian Islands campaign E20481 entity
Predicate countryInvolved P375 FINISHED
Object Japan E174 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: Japan | Statement: [Aleutian Islands campaign, countryInvolved, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japan
Context triple: [Aleutian Islands campaign, countryInvolved, Japan]
  • A. Japan chosen
    Japan is an East Asian island nation in the Pacific Ocean known for its advanced technology, rich cultural heritage, and major cities such as Tokyo, Osaka, and Kyoto.
  • B. Honshu
    Honshu is the largest and most populous island of Japan, home to major cities such as Tokyo, Osaka, and Kyoto.
  • C. South Korea
    South Korea is an East Asian nation on the southern half of the Korean Peninsula, known for its advanced technology, vibrant pop culture, and rapid economic development.
  • D. Fujinomiya, Japan
    Fujinomiya, Japan is a city in Shizuoka Prefecture known as a gateway to Mount Fuji and for its scenic views, shrines, and local cuisine.
  • E. Oppama, Japan
    Oppama, Japan is an industrial coastal district in Yokosuka, Kanagawa Prefecture, best known for its major Nissan automobile manufacturing plant.
  • 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_69a493b0f2fc81908cd227480a5356a1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3c191ac819099ebf3cb32f096d8 completed March 1, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16fdd37c81909262c1cc271cdd21 completed March 7, 2026, 12:15 p.m.
Created at: March 1, 2026, 7:40 p.m.