Triple

T1860601
Position Surface form Disambiguated ID Type / Status
Subject Taitō E34802 entity
Predicate hasHistoricDistrict P295 FINISHED
Object Ueno E151036 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: Ueno | Statement: [Taitō, hasHistoricDistrict, Ueno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ueno
Context triple: [Taitō, hasHistoricDistrict, Ueno]
  • A. Ueno chosen
    Ueno is a major district in Tokyo known for Ueno Park, its museums, zoo, and busy transportation hub.
  • B. Toyonaka
    Toyonaka is a suburban city in Japan’s Kansai region known for its residential neighborhoods, educational institutions, and proximity to central Osaka.
  • C. Asakusa
    Asakusa is a historic district in Tokyo best known for its ancient Sensō-ji Temple, traditional shopping streets, and preserved old-town atmosphere.
  • D. Fushimi
    Fushimi is a historic district in Kyoto, Japan, known for its castle and its association with key events and figures of the late Sengoku period.
  • E. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb09caee881908efe8aa38471298c completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108b7617c8190938c7ed35e0a791e completed March 11, 2026, 6:16 a.m.
Created at: March 4, 2026, 7:34 p.m.