Triple

T15664112
Position Surface form Disambiguated ID Type / Status
Subject Sakuragawa Station (Osaka) E376641 entity
Predicate locatedIn P40 FINISHED
Object Naniwa-ku NE NERFINISHED

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: Naniwa-ku | Statement: [Sakuragawa Station (Osaka), locatedIn, Naniwa-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naniwa-ku
Context triple: [Sakuragawa Station (Osaka), locatedIn, Naniwa-ku]
  • A. Naniwa-ku chosen
    Naniwa-ku is a central ward of Osaka, Japan, known for its bustling entertainment districts, shopping streets, and iconic landmarks such as Tsutenkaku Tower.
  • B. Nishinari-ku
    Nishinari-ku is a ward in Osaka, Japan, known for its dense urban environment, working-class neighborhoods, and historically being one of the city's poorest districts.
  • C. Nakahara-ku
    Nakahara-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known as a residential and commercial area within the Greater Tokyo metropolitan region.
  • D. Izumi-ku
    Izumi-ku is a northern residential and commercial ward of Sendai in Miyagi Prefecture, Japan, known for its suburban neighborhoods and shopping centers.
  • E. Taihaku-ku
    Taihaku-ku is a ward in the city of Sendai, Japan, known for its mix of residential areas, natural scenery, and hot spring resorts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f0f4df08190ad2c5d78e435d8eb completed April 16, 2026, 2:53 a.m.
Created at: April 10, 2026, 4:16 a.m.