Triple

T7606919
Position Surface form Disambiguated ID Type / Status
Subject Toyooka E180128 entity
Predicate partOf P40 FINISHED
Object Sanin region E425361 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: Sanin region | Statement: [Toyooka, partOf, Sanin region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sanin region
Context triple: [Toyooka, partOf, Sanin region]
  • A. San’in region chosen
    The San’in region is a coastal area along the Sea of Japan in western Honshu, known for its rural landscapes, historic towns, and relatively cooler, cloudier climate compared to other parts of Japan.
  • B. Geita Region
    Geita Region is an administrative region in northwestern Tanzania, known for its significant gold mining activities and proximity to Lake Victoria.
  • C. Chikuho region
    The Chikuho region is a former coal-mining area in central Fukuoka Prefecture, Japan, known for its industrial history and working-class culture.
  • D. Tajima region
    The Tajima region is a northern area of Hyōgo Prefecture in Japan, known for its rural landscapes, hot springs, and the origin of the famed Tajima-gyu cattle used for Kobe beef.
  • E. Oshikoto Region
    Oshikoto Region is an administrative region in northern Namibia known for its mix of rural communities, agriculture, and the town of Tsumeb as its economic 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9fe10408190b1c12bb8f911cea8 completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86857db14819086d5ebd825d30e77 completed March 28, 2026, 11:46 p.m.
Created at: March 27, 2026, 3:54 p.m.