Triple

T2984601
Position Surface form Disambiguated ID Type / Status
Subject Muroran E80590 entity
Predicate hasSisterCity P919 FINISHED
Object Joetsu E27598 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: Joetsu | Statement: [Muroran, hasSisterCity, Joetsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joetsu
Context triple: [Muroran, hasSisterCity, Joetsu]
  • A. Asahikawa
    Asahikawa is a major city in central Hokkaido, Japan, known for its cold winters, Asahiyama Zoo, and role as a regional commercial and transportation hub.
  • B. Utsunomiya
    Utsunomiya is a city in Tochigi Prefecture, Japan, known as a regional commercial center and for its specialty gyoza (dumplings).
  • C. Takayama
    Takayama is a historic mountain city in Japan’s Gifu Prefecture, known for its well-preserved Edo-period streets, traditional wooden houses, and proximity to the Japanese Alps.
  • D. Niigata chosen
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • E. Semboku
    Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c65ad0819087bb4ae92ab0dc55 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cb9f421081908b9df22decae8923 completed March 28, 2026, 12:37 p.m.
Created at: March 8, 2026, 2:59 p.m.