Triple

T978177
Position Surface form Disambiguated ID Type / Status
Subject Great Hanshin earthquake E21104 entity
Predicate affectedCity P10973 FINISHED
Object Ashiya E134179 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: Ashiya | Statement: [Great Hanshin earthquake, affectedCity, Ashiya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ashiya
Context triple: [Great Hanshin earthquake, affectedCity, Ashiya]
  • A. Ashiya chosen
    Ashiya is an affluent coastal city in Japan’s Hyōgo Prefecture, known for its upscale residential neighborhoods and proximity to both Kobe and Osaka.
  • B. Maishima
    Maishima is a man-made island in Osaka, Japan, known for its sports facilities, event venues, and waterfront recreational areas.
  • C. Tokushima
    Tokushima is a coastal city on Japan’s Shikoku Island known for its annual Awa Odori dance festival and role as a regional cultural and economic center.
  • D. Kyotanabe
    Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
  • E. Omiya
    Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
  • 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_69a493c2b62c8190b616351789ec47f8 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b47861808190be56a7bbd926e658 completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69af8309912c819096cf0dad7039ec95 completed March 10, 2026, 2:33 a.m.
Created at: March 1, 2026, 7:40 p.m.