Triple

T51549
Position Surface form Disambiguated ID Type / Status
Subject Fumio Kishida E1011 entity
Predicate countryOfCitizenship P2 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: [Fumio Kishida, countryOfCitizenship, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japan
Context triple: [Fumio Kishida, countryOfCitizenship, 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. 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.
  • E. Hokkaido
    Hokkaido is Japan’s northernmost main island, known for its cold climate, vast natural landscapes, and popular ski resorts.
  • 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_69a2480baefc81909951b14058479aa2 completed Feb. 28, 2026, 1:42 a.m.
NER Named-entity recognition batch_69a24b0382b48190a7ca80ade6d2e270 completed Feb. 28, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35e9e2b8c8190913c083e841c98d8 completed Feb. 28, 2026, 9:31 p.m.
Created at: Feb. 28, 2026, 1:47 a.m.