Triple

T9893797
Position Surface form Disambiguated ID Type / Status
Subject Mount Hiei E181518 entity
Predicate offersViewOf P3821 FINISHED
Object Kyoto city E10010 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: Kyoto city | Statement: [Mount Hiei, offersViewOf, Kyoto city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyoto city
Context triple: [Mount Hiei, offersViewOf, Kyoto city]
  • A. Kyoto chosen
    Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
  • B. Osaka and Kyoto
    Osaka and Kyoto are two major cities in Japan’s Kansai region, renowned respectively for modern urban culture and historic temples, shrines, and traditional architecture.
  • C. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • D. Himeji
    Himeji is a historic Japanese city best known for Himeji Castle, a UNESCO World Heritage Site and one of Japan’s most iconic and well-preserved feudal castles.
  • E. Fuji City
    Fuji City is an industrial city in Shizuoka Prefecture, Japan, known for its paper manufacturing industry and views of nearby Mount Fuji.
  • 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_69ca8283a6708190801af7a25a7ebb9f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb48271d48190b718c7f6b2fe315b completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d96af89e48819093a6c149ac988391 completed April 10, 2026, 9:26 p.m.
Created at: March 30, 2026, 8:39 p.m.