Triple

T7192153
Position Surface form Disambiguated ID Type / Status
Subject Otsu E167718 entity
Predicate near P350 FINISHED
Object Kyoto 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 | Statement: [Otsu, near, Kyoto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyoto
Context triple: [Otsu, near, Kyoto]
  • 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
    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.
  • C. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • 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. Matsumoto
    Matsumoto is a historic city in central Japan best known for its well-preserved Matsumoto Castle and as a gateway to the scenic Japanese Alps.
  • 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_69c6888b5248819090499a884ee3ec39 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e901ea1481908a9e44f96dd4b553 completed March 27, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bf709c4c819090c35eb41f46f5d2 completed March 28, 2026, 11:45 a.m.
Created at: March 27, 2026, 2:50 p.m.