Triple

T2655846
Position Surface form Disambiguated ID Type / Status
Subject Kyoto Station E54607 entity
Predicate locatedIn P40 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: [Kyoto Station, locatedIn, Kyoto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyoto
Context triple: [Kyoto Station, locatedIn, 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. 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.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd933ec008190aef1442460c4cfbc completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69b12de0989481909ce71f3fb739ac2a completed March 11, 2026, 8:54 a.m.
Created at: March 6, 2026, 9:53 p.m.