Triple

T2080293
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Education, Kyoto University E45223 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: [Faculty of Education, Kyoto University, locatedIn, Kyoto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyoto
Context triple: [Faculty of Education, Kyoto University, 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_69a8891869c88190a02643e3bb746f59 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba345be48190a1895f388e7749e5 completed March 7, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108b7617c8190938c7ed35e0a791e completed March 11, 2026, 6:16 a.m.
Created at: March 4, 2026, 7:41 p.m.