Triple

T981993
Position Surface form Disambiguated ID Type / Status
Subject JR Yumesaki Line E21188 entity
Predicate regionServed P82 FINISHED
Object Konohana Ward, Osaka E279263 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: Konohana Ward, Osaka | Statement: [JR Yumesaki Line, regionServed, Konohana Ward, Osaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konohana Ward, Osaka
Context triple: [JR Yumesaki Line, regionServed, Konohana Ward, Osaka]
  • A. Konohana-ku, Osaka chosen
    Konohana-ku, Osaka is a ward of Osaka City in Japan known for hosting major attractions like Universal Studios Japan and its themed entertainment areas.
  • B. Yodogawa-ku, Osaka
    Yodogawa-ku, Osaka is a ward in northern Osaka City known as a major transportation hub, notably hosting Shin-Osaka Station, the city’s primary Shinkansen terminal.
  • C. Tennoji-ku, Osaka
    Tennoji-ku, Osaka is a central ward of Osaka City known for its major transport hub, historic Shitenno-ji Temple, and large commercial and shopping complexes.
  • D. Chuo-ku, Osaka
    Chuo-ku, Osaka is a central ward of Osaka City known as a major commercial, business, and entertainment hub.
  • E. Umeda, Osaka
    Umeda, Osaka is a major commercial and transportation district in Osaka, Japan, known for its dense cluster of department stores, office towers, and railway terminals.
  • 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_69a4b47cbca48190a01880bb411e80bd completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69afa0333e40819086d963491946e28b completed March 10, 2026, 4:38 a.m.
Created at: March 1, 2026, 7:41 p.m.